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Author

*The author of this computation has been verified*

R Software Module

rwasp_regression_trees1.wasp

Title produced by software

Recursive Partitioning (Regression Trees)

Date of computation

Wed, 21 Dec 2011 10:25:25 -0500

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Dec/21/t1324481145clduqrgigs6ceva.htm/, Retrieved Tue, 07 May 2024 21:19:44 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=158821, Retrieved Tue, 07 May 2024 21:19:44 +0000

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No (this computation is public)

User-defined keywords

Estimated Impact

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-     [Kendall tau Correlation Matrix] [] [2011-12-21 14:41:59] [6f7edaad2006217944933c2855224291]
- RMP     [Recursive Partitioning (Regression Trees)] [] [2011-12-21 15:25:25] [4126eca3aa45270aa47093f41b7f56ff] [Current]

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Dataseries X:

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Histogram

Boxplots

115	1418	210907	81	79	56
109	869	120982	55	58	56
146	1530	176508	50	60	54
116	2172	179321	125	108	89
68	901	123185	40	49	40
101	463	52746	37	0	25
96	3201	385534	63	121	92
67	371	33170	44	1	18
44	1192	101645	88	20	63
100	1583	149061	66	43	44
93	1439	165446	57	69	33
140	1764	237213	74	78	84
166	1495	173326	49	86	88
99	1373	133131	52	44	55
139	2187	258873	88	104	60
130	1491	180083	36	63	66
181	4041	324799	108	158	154
116	1706	230964	43	102	53
116	2152	236785	75	77	119
88	1036	135473	32	82	41
139	1882	202925	44	115	61
135	1929	215147	85	101	58
108	2242	344297	86	80	75
89	1220	153935	56	50	33
156	1289	132943	50	83	40
129	2515	174724	135	123	92
118	2147	174415	63	73	100
118	2352	225548	81	81	112
125	1638	223632	52	105	73
95	1222	124817	44	47	40
126	1812	221698	113	105	45
135	1677	210767	39	94	60
154	1579	170266	73	44	62
165	1731	260561	48	114	75
113	807	84853	33	38	31
127	2452	294424	59	107	77
52	829	101011	41	30	34
121	1940	215641	69	71	46
136	2662	325107	64	84	99
0	186	7176	1	0	17
108	1499	167542	59	59	66
46	865	106408	32	33	30
54	1793	96560	129	42	76
124	2527	265769	37	96	146
115	2747	269651	31	106	67
128	1324	149112	65	56	56
80	2702	175824	107	57	107
97	1383	152871	74	59	58
104	1179	111665	54	39	34
59	2099	116408	76	34	61
125	4308	362301	715	76	119
82	918	78800	57	20	42
149	1831	183167	66	91	66
149	3373	277965	106	115	89
122	1713	150629	54	85	44
118	1438	168809	32	76	66
12	496	24188	20	8	24
144	2253	329267	71	79	259
67	744	65029	21	21	17
52	1161	101097	70	30	64
108	2352	218946	112	76	41
166	2144	244052	66	101	68
80	4691	341570	190	94	168
60	1112	103597	66	27	43
107	2694	233328	165	92	132
127	1973	256462	56	123	105
107	1769	206161	61	75	71
146	3148	311473	53	128	112
84	2474	235800	127	105	94
141	2084	177939	63	55	82
123	1954	207176	38	56	70
111	1226	196553	50	41	57
98	1389	174184	52	72	53
105	1496	143246	42	67	103
135	2269	187559	76	75	121
107	1833	187681	67	114	62
85	1268	119016	50	118	52
155	1943	182192	53	77	52
88	893	73566	39	22	32
155	1762	194979	50	66	62
104	1403	167488	77	69	45
132	1425	143756	57	105	46
127	1857	275541	73	116	63
108	1840	243199	34	88	75
129	1502	182999	39	73	88
116	1441	135649	46	99	46
122	1420	152299	63	62	53
85	1416	120221	35	53	37
147	2970	346485	106	118	90
99	1317	145790	43	30	63
87	1644	193339	47	100	78
28	870	80953	31	49	25
90	1654	122774	162	24	45
109	1054	130585	57	67	46
78	937	112611	36	46	41
111	3004	286468	263	57	144
158	2008	241066	78	75	82
141	2547	148446	63	135	91
122	1885	204713	54	68	71
124	1626	182079	63	124	63
93	1468	140344	77	33	53
124	2445	220516	79	98	62
112	1964	243060	110	58	63
108	1381	162765	56	68	32
99	1369	182613	56	81	39
117	1659	232138	43	131	62
199	2888	265318	111	110	117
78	1290	85574	71	37	34
91	2845	310839	62	130	92
158	1982	225060	56	93	93
126	1904	232317	74	118	54
122	1391	144966	60	39	144
71	602	43287	43	13	14
75	1743	155754	68	74	61
115	1559	164709	53	81	109
119	2014	201940	87	109	38
124	2143	235454	46	151	73
72	2146	220801	105	51	75
91	874	99466	32	28	50
45	1590	92661	133	40	61
78	1590	133328	79	56	55
39	1210	61361	51	27	77
68	2072	125930	207	37	75
119	1281	100750	67	83	72
117	1401	224549	47	54	50
39	834	82316	34	27	32
50	1105	102010	66	28	53
88	1272	101523	76	59	42
155	1944	243511	65	133	71
0	391	22938	9	12	10
36	761	41566	42	0	35
123	1605	152474	45	106	65
32	530	61857	25	23	25
99	1988	99923	115	44	66
136	1386	132487	97	71	41
117	2395	317394	53	116	86
0	387	21054	2	4	16
88	1742	209641	52	62	42
39	620	22648	44	12	19
25	449	31414	22	18	19
52	800	46698	35	14	45
75	1684	131698	74	60	65
71	1050	91735	103	7	35
124	2699	244749	144	98	95
151	1606	184510	60	64	49
71	1502	79863	134	29	37
145	1204	128423	89	32	64
87	1138	97839	42	25	38
27	568	38214	52	16	34
131	1459	151101	98	48	32
162	2158	272458	99	100	65
165	1111	172494	52	46	52
54	1421	108043	29	45	62
159	2833	328107	125	129	65
147	1955	250579	106	130	83
170	2922	351067	95	136	95
119	1002	158015	40	59	29
49	1060	98866	140	25	18
104	956	85439	43	32	33
120	2186	229242	128	63	247
150	3604	351619	142	95	139
112	1035	84207	73	14	29
59	1417	120445	72	36	118
136	3261	324598	128	113	110
107	1587	131069	61	47	67
130	1424	204271	73	92	42
115	1701	165543	148	70	65
107	1249	141722	64	19	94
75	946	116048	45	50	64
71	1926	250047	58	41	81
120	3352	299775	97	91	95
116	1641	195838	50	111	67
79	2035	173260	37	41	63
150	2312	254488	50	120	83
156	1369	104389	105	135	45
51	1577	136084	69	27	30
118	2201	199476	46	87	70
71	961	92499	57	25	32
144	1900	224330	52	131	83
47	1254	135781	98	45	31
28	1335	74408	61	29	67
68	1597	81240	89	58	66
0	207	14688	0	4	10
110	1645	181633	48	47	70
147	2429	271856	91	109	103
0	151	7199	0	7	5
15	474	46660	7	12	20
4	141	17547	3	0	5
64	1639	133368	54	37	36
111	872	95227	70	37	34
85	1318	152601	36	46	48
68	1018	98146	37	15	40
40	1383	79619	123	42	43
80	1314	59194	247	7	31
88	1335	139942	46	54	42
48	1403	118612	72	54	46
76	910	72880	41	14	33
51	616	65475	24	16	18
67	1407	99643	45	33	55
59	771	71965	33	32	35
61	766	77272	27	21	59
76	473	49289	36	15	19
60	1376	135131	87	38	66
68	1232	108446	90	22	60
71	1521	89746	114	28	36
76	572	44296	31	10	25
62	1059	77648	45	31	47
61	1544	181528	69	32	54
67	1230	134019	51	32	53
88	1206	124064	34	43	40
30	1205	92630	60	27	40
64	1255	121848	45	37	39
68	613	52915	54	20	14
64	721	81872	25	32	45
91	1109	58981	38	0	36
88	740	53515	52	5	28
52	1126	60812	67	26	44
49	728	56375	74	10	30
62	689	65490	38	27	22
61	592	80949	30	11	17
76	995	76302	26	29	31
88	1613	104011	67	25	55
66	2048	98104	132	55	54
71	705	67989	42	23	21
68	301	30989	35	5	14
48	1803	135458	118	43	81
25	799	73504	68	23	35
68	861	63123	43	34	43
41	1186	61254	76	36	46
90	1451	74914	64	35	30
66	628	31774	48	0	23
54	1161	81437	64	37	38
59	1463	87186	56	28	54
60	742	50090	71	16	20
77	979	65745	75	26	53
68	675	56653	39	38	45
72	1241	158399	42	23	39
67	676	46455	39	22	20
64	1049	73624	93	30	24
63	620	38395	38	16	31
59	1081	91899	60	18	35
84	1688	139526	71	28	151
64	736	52164	52	32	52
56	617	51567	27	21	30
54	812	70551	59	23	31
67	1051	84856	40	29	29
58	1656	102538	79	50	57
59	705	86678	44	12	40
40	945	85709	65	21	44
22	554	34662	10	18	25
83	1597	150580	124	27	77
81	982	99611	81	41	35
2	222	19349	15	13	11
72	1212	99373	92	12	63
61	1143	86230	42	21	44
15	435	30837	10	8	19
32	532	31706	24	26	13
62	882	89806	64	27	42
58	608	62088	45	13	38
36	459	40151	22	16	29
59	578	27634	56	2	20
68	826	76990	94	42	27
21	509	37460	19	5	20
55	717	54157	35	37	19
54	637	49862	32	17	37
55	857	84337	35	38	26
72	830	64175	48	37	42
41	652	59382	49	29	49
61	707	119308	48	32	30
67	954	76702	62	35	49
76	1461	103425	96	17	67
64	672	70344	45	20	28
3	778	43410	63	7	19
63	1141	104838	71	46	49
40	680	62215	26	24	27
69	1090	69304	48	40	30
48	616	53117	29	3	22
8	285	19764	19	10	12
52	1145	86680	45	37	31
66	733	84105	45	17	20
76	888	77945	67	28	20
43	849	89113	30	19	39
39	1182	91005	36	29	29
14	528	40248	34	8	16
61	642	64187	36	10	27
71	947	50857	34	15	21
44	819	56613	37	15	19
60	757	62792	46	28	35
64	894	72535	44	17	14

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	5 seconds
R Server	'Herman Ole Andreas Wold' @ wold.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 5 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=158821&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]5 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=158821&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=158821&T=0

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	5 seconds
R Server	'Herman Ole Andreas Wold' @ wold.wessa.net

Goodness of Fit
Correlation	0.8445
R-squared	0.7132
RMSE	21.4997

\begin{tabular}{lllllllll}
\hline
Goodness of Fit \tabularnewline
Correlation & 0.8445 \tabularnewline
R-squared & 0.7132 \tabularnewline
RMSE & 21.4997 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=158821&T=1

[TABLE]
[ROW][C]Goodness of Fit[/C][/ROW]
[ROW][C]Correlation[/C][C]0.8445[/C][/ROW]
[ROW][C]R-squared[/C][C]0.7132[/C][/ROW]
[ROW][C]RMSE[/C][C]21.4997[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=158821&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=158821&T=1

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Goodness of Fit
Correlation	0.8445
R-squared	0.7132
RMSE	21.4997

Actuals, Predictions, and Residuals
#	Actuals	Forecasts	Residuals
1	115	129.75	-14.75
2	109	109.942857142857	-0.942857142857136
3	146	109.942857142857	36.0571428571429
4	116	129.75	-13.75
5	68	65.2125984251968	2.78740157480316
6	101	65.2125984251968	35.7874015748032
7	96	129.75	-33.75
8	67	49.9	17.1
9	44	65.2125984251968	-21.2125984251968
10	100	99.6666666666667	0.333333333333329
11	93	109.942857142857	-16.9428571428571
12	140	129.75	10.25
13	166	129.75	36.25
14	99	65.2125984251968	33.7874015748032
15	139	129.75	9.25
16	130	109.942857142857	20.0571428571429
17	181	129.75	51.25
18	116	129.75	-13.75
19	116	129.75	-13.75
20	88	129.75	-41.75
21	139	129.75	9.25
22	135	129.75	5.25
23	108	129.75	-21.75
24	89	99.6666666666667	-10.6666666666667
25	156	129.75	26.25
26	129	129.75	-0.75
27	118	109.942857142857	8.05714285714286
28	118	129.75	-11.75
29	125	129.75	-4.75
30	95	65.2125984251968	29.7874015748032
31	126	129.75	-3.75
32	135	129.75	5.25
33	154	99.6666666666667	54.3333333333333
34	165	129.75	35.25
35	113	65.2125984251968	47.7874015748032
36	127	129.75	-2.75
37	52	65.2125984251968	-13.2125984251968
38	121	109.942857142857	11.0571428571429
39	136	129.75	6.25
40	0	11.9375	-11.9375
41	108	109.942857142857	-1.94285714285714
42	46	65.2125984251968	-19.2125984251968
43	54	65.2125984251968	-11.2125984251968
44	124	129.75	-5.75
45	115	129.75	-14.75
46	128	109.942857142857	18.0571428571429
47	80	109.942857142857	-29.9428571428571
48	97	109.942857142857	-12.9428571428571
49	104	65.2125984251968	38.7874015748032
50	59	65.2125984251968	-6.21259842519684
51	125	129.75	-4.75
52	82	65.2125984251968	16.7874015748032
53	149	129.75	19.25
54	149	129.75	19.25
55	122	129.75	-7.75
56	118	129.75	-11.75
57	12	11.9375	0.0625
58	144	129.75	14.25
59	67	65.2125984251968	1.78740157480316
60	52	65.2125984251968	-13.2125984251968
61	108	129.75	-21.75
62	166	129.75	36.25
63	80	129.75	-49.75
64	60	65.2125984251968	-5.21259842519684
65	107	129.75	-22.75
66	127	129.75	-2.75
67	107	129.75	-22.75
68	146	129.75	16.25
69	84	129.75	-45.75
70	141	109.942857142857	31.0571428571429
71	123	109.942857142857	13.0571428571429
72	111	99.6666666666667	11.3333333333333
73	98	109.942857142857	-11.9428571428571
74	105	109.942857142857	-4.94285714285714
75	135	129.75	5.25
76	107	129.75	-22.75
77	85	129.75	-44.75
78	155	129.75	25.25
79	88	65.2125984251968	22.7874015748032
80	155	109.942857142857	45.0571428571429
81	104	109.942857142857	-5.94285714285714
82	132	129.75	2.25
83	127	129.75	-2.75
84	108	129.75	-21.75
85	129	109.942857142857	19.0571428571429
86	116	129.75	-13.75
87	122	109.942857142857	12.0571428571429
88	85	65.2125984251968	19.7874015748032
89	147	129.75	17.25
90	99	99.6666666666667	-0.666666666666671
91	87	129.75	-42.75
92	28	65.2125984251968	-37.2125984251968
93	90	65.2125984251968	24.7874015748032
94	109	109.942857142857	-0.942857142857136
95	78	65.2125984251968	12.7874015748032
96	111	109.942857142857	1.05714285714286
97	158	129.75	28.25
98	141	129.75	11.25
99	122	109.942857142857	12.0571428571429
100	124	129.75	-5.75
101	93	99.6666666666667	-6.66666666666667
102	124	129.75	-5.75
103	112	109.942857142857	2.05714285714286
104	108	109.942857142857	-1.94285714285714
105	99	129.75	-30.75
106	117	129.75	-12.75
107	199	129.75	69.25
108	78	65.2125984251968	12.7874015748032
109	91	129.75	-38.75
110	158	129.75	28.25
111	126	129.75	-3.75
112	122	99.6666666666667	22.3333333333333
113	71	49.9	21.1
114	75	109.942857142857	-34.9428571428571
115	115	129.75	-14.75
116	119	129.75	-10.75
117	124	129.75	-5.75
118	72	99.6666666666667	-27.6666666666667
119	91	65.2125984251968	25.7874015748032
120	45	65.2125984251968	-20.2125984251968
121	78	109.942857142857	-31.9428571428571
122	39	65.2125984251968	-26.2125984251968
123	68	65.2125984251968	2.78740157480316
124	119	129.75	-10.75
125	117	99.6666666666667	17.3333333333333
126	39	65.2125984251968	-26.2125984251968
127	50	65.2125984251968	-15.2125984251968
128	88	109.942857142857	-21.9428571428571
129	155	129.75	25.25
130	0	11.9375	-11.9375
131	36	49.9	-13.9
132	123	129.75	-6.75
133	32	65.2125984251968	-33.2125984251968
134	99	65.2125984251968	33.7874015748032
135	136	109.942857142857	26.0571428571429
136	117	129.75	-12.75
137	0	11.9375	-11.9375
138	88	109.942857142857	-21.9428571428571
139	39	49.9	-10.9
140	25	11.9375	13.0625
141	52	65.2125984251968	-13.2125984251968
142	75	109.942857142857	-34.9428571428571
143	71	65.2125984251968	5.78740157480316
144	124	129.75	-5.75
145	151	109.942857142857	41.0571428571429
146	71	65.2125984251968	5.78740157480316
147	145	65.2125984251968	79.7874015748032
148	87	65.2125984251968	21.7874015748032
149	27	49.9	-22.9
150	131	99.6666666666667	31.3333333333333
151	162	129.75	32.25
152	165	99.6666666666667	65.3333333333333
153	54	65.2125984251968	-11.2125984251968
154	159	129.75	29.25
155	147	129.75	17.25
156	170	129.75	40.25
157	119	109.942857142857	9.05714285714286
158	49	65.2125984251968	-16.2125984251968
159	104	65.2125984251968	38.7874015748032
160	120	109.942857142857	10.0571428571429
161	150	129.75	20.25
162	112	65.2125984251968	46.7874015748032
163	59	65.2125984251968	-6.21259842519684
164	136	129.75	6.25
165	107	65.2125984251968	41.7874015748032
166	130	129.75	0.25
167	115	109.942857142857	5.05714285714286
168	107	99.6666666666667	7.33333333333333
169	75	65.2125984251968	9.78740157480316
170	71	99.6666666666667	-28.6666666666667
171	120	129.75	-9.75
172	116	129.75	-13.75
173	79	99.6666666666667	-20.6666666666667
174	150	129.75	20.25
175	156	129.75	26.25
176	51	65.2125984251968	-14.2125984251968
177	118	129.75	-11.75
178	71	65.2125984251968	5.78740157480316
179	144	129.75	14.25
180	47	65.2125984251968	-18.2125984251968
181	28	65.2125984251968	-37.2125984251968
182	68	109.942857142857	-41.9428571428571
183	0	11.9375	-11.9375
184	110	99.6666666666667	10.3333333333333
185	147	129.75	17.25
186	0	11.9375	-11.9375
187	15	65.2125984251968	-50.2125984251968
188	4	11.9375	-7.9375
189	64	65.2125984251968	-1.21259842519684
190	111	65.2125984251968	45.7874015748032
191	85	99.6666666666667	-14.6666666666667
192	68	65.2125984251968	2.78740157480316
193	40	65.2125984251968	-25.2125984251968
194	80	65.2125984251968	14.7874015748032
195	88	99.6666666666667	-11.6666666666667
196	48	65.2125984251968	-17.2125984251968
197	76	65.2125984251968	10.7874015748032
198	51	65.2125984251968	-14.2125984251968
199	67	65.2125984251968	1.78740157480316
200	59	65.2125984251968	-6.21259842519684
201	61	65.2125984251968	-4.21259842519684
202	76	65.2125984251968	10.7874015748032
203	60	65.2125984251968	-5.21259842519684
204	68	65.2125984251968	2.78740157480316
205	71	65.2125984251968	5.78740157480316
206	76	65.2125984251968	10.7874015748032
207	62	65.2125984251968	-3.21259842519684
208	61	99.6666666666667	-38.6666666666667
209	67	65.2125984251968	1.78740157480316
210	88	65.2125984251968	22.7874015748032
211	30	65.2125984251968	-35.2125984251968
212	64	65.2125984251968	-1.21259842519684
213	68	65.2125984251968	2.78740157480316
214	64	65.2125984251968	-1.21259842519684
215	91	65.2125984251968	25.7874015748032
216	88	65.2125984251968	22.7874015748032
217	52	65.2125984251968	-13.2125984251968
218	49	65.2125984251968	-16.2125984251968
219	62	65.2125984251968	-3.21259842519684
220	61	65.2125984251968	-4.21259842519684
221	76	65.2125984251968	10.7874015748032
222	88	65.2125984251968	22.7874015748032
223	66	109.942857142857	-43.9428571428571
224	71	65.2125984251968	5.78740157480316
225	68	49.9	18.1
226	48	65.2125984251968	-17.2125984251968
227	25	65.2125984251968	-40.2125984251968
228	68	65.2125984251968	2.78740157480316
229	41	65.2125984251968	-24.2125984251968
230	90	65.2125984251968	24.7874015748032
231	66	49.9	16.1
232	54	65.2125984251968	-11.2125984251968
233	59	65.2125984251968	-6.21259842519684
234	60	65.2125984251968	-5.21259842519684
235	77	65.2125984251968	11.7874015748032
236	68	65.2125984251968	2.78740157480316
237	72	99.6666666666667	-27.6666666666667
238	67	65.2125984251968	1.78740157480316
239	64	65.2125984251968	-1.21259842519684
240	63	49.9	13.1
241	59	65.2125984251968	-6.21259842519684
242	84	99.6666666666667	-15.6666666666667
243	64	65.2125984251968	-1.21259842519684
244	56	65.2125984251968	-9.21259842519684
245	54	65.2125984251968	-11.2125984251968
246	67	65.2125984251968	1.78740157480316
247	58	65.2125984251968	-7.21259842519684
248	59	65.2125984251968	-6.21259842519684
249	40	65.2125984251968	-25.2125984251968
250	22	11.9375	10.0625
251	83	99.6666666666667	-16.6666666666667
252	81	65.2125984251968	15.7874015748032
253	2	11.9375	-9.9375
254	72	65.2125984251968	6.78740157480316
255	61	65.2125984251968	-4.21259842519684
256	15	11.9375	3.0625
257	32	11.9375	20.0625
258	62	65.2125984251968	-3.21259842519684
259	58	65.2125984251968	-7.21259842519684
260	36	11.9375	24.0625
261	59	49.9	9.1
262	68	65.2125984251968	2.78740157480316
263	21	11.9375	9.0625
264	55	65.2125984251968	-10.2125984251968
265	54	65.2125984251968	-11.2125984251968
266	55	65.2125984251968	-10.2125984251968
267	72	65.2125984251968	6.78740157480316
268	41	65.2125984251968	-24.2125984251968
269	61	65.2125984251968	-4.21259842519684
270	67	65.2125984251968	1.78740157480316
271	76	65.2125984251968	10.7874015748032
272	64	65.2125984251968	-1.21259842519684
273	3	49.9	-46.9
274	63	65.2125984251968	-2.21259842519684
275	40	65.2125984251968	-25.2125984251968
276	69	65.2125984251968	3.78740157480316
277	48	65.2125984251968	-17.2125984251968
278	8	11.9375	-3.9375
279	52	65.2125984251968	-13.2125984251968
280	66	65.2125984251968	0.787401574803155
281	76	65.2125984251968	10.7874015748032
282	43	65.2125984251968	-22.2125984251968
283	39	65.2125984251968	-26.2125984251968
284	14	11.9375	2.0625
285	61	65.2125984251968	-4.21259842519684
286	71	65.2125984251968	5.78740157480316
287	44	65.2125984251968	-21.2125984251968
288	60	65.2125984251968	-5.21259842519684
289	64	65.2125984251968	-1.21259842519684

\begin{tabular}{lllllllll}
\hline
Actuals, Predictions, and Residuals \tabularnewline
# & Actuals & Forecasts & Residuals \tabularnewline
1 & 115 & 129.75 & -14.75 \tabularnewline
2 & 109 & 109.942857142857 & -0.942857142857136 \tabularnewline
3 & 146 & 109.942857142857 & 36.0571428571429 \tabularnewline
4 & 116 & 129.75 & -13.75 \tabularnewline
5 & 68 & 65.2125984251968 & 2.78740157480316 \tabularnewline
6 & 101 & 65.2125984251968 & 35.7874015748032 \tabularnewline
7 & 96 & 129.75 & -33.75 \tabularnewline
8 & 67 & 49.9 & 17.1 \tabularnewline
9 & 44 & 65.2125984251968 & -21.2125984251968 \tabularnewline
10 & 100 & 99.6666666666667 & 0.333333333333329 \tabularnewline
11 & 93 & 109.942857142857 & -16.9428571428571 \tabularnewline
12 & 140 & 129.75 & 10.25 \tabularnewline
13 & 166 & 129.75 & 36.25 \tabularnewline
14 & 99 & 65.2125984251968 & 33.7874015748032 \tabularnewline
15 & 139 & 129.75 & 9.25 \tabularnewline
16 & 130 & 109.942857142857 & 20.0571428571429 \tabularnewline
17 & 181 & 129.75 & 51.25 \tabularnewline
18 & 116 & 129.75 & -13.75 \tabularnewline
19 & 116 & 129.75 & -13.75 \tabularnewline
20 & 88 & 129.75 & -41.75 \tabularnewline
21 & 139 & 129.75 & 9.25 \tabularnewline
22 & 135 & 129.75 & 5.25 \tabularnewline
23 & 108 & 129.75 & -21.75 \tabularnewline
24 & 89 & 99.6666666666667 & -10.6666666666667 \tabularnewline
25 & 156 & 129.75 & 26.25 \tabularnewline
26 & 129 & 129.75 & -0.75 \tabularnewline
27 & 118 & 109.942857142857 & 8.05714285714286 \tabularnewline
28 & 118 & 129.75 & -11.75 \tabularnewline
29 & 125 & 129.75 & -4.75 \tabularnewline
30 & 95 & 65.2125984251968 & 29.7874015748032 \tabularnewline
31 & 126 & 129.75 & -3.75 \tabularnewline
32 & 135 & 129.75 & 5.25 \tabularnewline
33 & 154 & 99.6666666666667 & 54.3333333333333 \tabularnewline
34 & 165 & 129.75 & 35.25 \tabularnewline
35 & 113 & 65.2125984251968 & 47.7874015748032 \tabularnewline
36 & 127 & 129.75 & -2.75 \tabularnewline
37 & 52 & 65.2125984251968 & -13.2125984251968 \tabularnewline
38 & 121 & 109.942857142857 & 11.0571428571429 \tabularnewline
39 & 136 & 129.75 & 6.25 \tabularnewline
40 & 0 & 11.9375 & -11.9375 \tabularnewline
41 & 108 & 109.942857142857 & -1.94285714285714 \tabularnewline
42 & 46 & 65.2125984251968 & -19.2125984251968 \tabularnewline
43 & 54 & 65.2125984251968 & -11.2125984251968 \tabularnewline
44 & 124 & 129.75 & -5.75 \tabularnewline
45 & 115 & 129.75 & -14.75 \tabularnewline
46 & 128 & 109.942857142857 & 18.0571428571429 \tabularnewline
47 & 80 & 109.942857142857 & -29.9428571428571 \tabularnewline
48 & 97 & 109.942857142857 & -12.9428571428571 \tabularnewline
49 & 104 & 65.2125984251968 & 38.7874015748032 \tabularnewline
50 & 59 & 65.2125984251968 & -6.21259842519684 \tabularnewline
51 & 125 & 129.75 & -4.75 \tabularnewline
52 & 82 & 65.2125984251968 & 16.7874015748032 \tabularnewline
53 & 149 & 129.75 & 19.25 \tabularnewline
54 & 149 & 129.75 & 19.25 \tabularnewline
55 & 122 & 129.75 & -7.75 \tabularnewline
56 & 118 & 129.75 & -11.75 \tabularnewline
57 & 12 & 11.9375 & 0.0625 \tabularnewline
58 & 144 & 129.75 & 14.25 \tabularnewline
59 & 67 & 65.2125984251968 & 1.78740157480316 \tabularnewline
60 & 52 & 65.2125984251968 & -13.2125984251968 \tabularnewline
61 & 108 & 129.75 & -21.75 \tabularnewline
62 & 166 & 129.75 & 36.25 \tabularnewline
63 & 80 & 129.75 & -49.75 \tabularnewline
64 & 60 & 65.2125984251968 & -5.21259842519684 \tabularnewline
65 & 107 & 129.75 & -22.75 \tabularnewline
66 & 127 & 129.75 & -2.75 \tabularnewline
67 & 107 & 129.75 & -22.75 \tabularnewline
68 & 146 & 129.75 & 16.25 \tabularnewline
69 & 84 & 129.75 & -45.75 \tabularnewline
70 & 141 & 109.942857142857 & 31.0571428571429 \tabularnewline
71 & 123 & 109.942857142857 & 13.0571428571429 \tabularnewline
72 & 111 & 99.6666666666667 & 11.3333333333333 \tabularnewline
73 & 98 & 109.942857142857 & -11.9428571428571 \tabularnewline
74 & 105 & 109.942857142857 & -4.94285714285714 \tabularnewline
75 & 135 & 129.75 & 5.25 \tabularnewline
76 & 107 & 129.75 & -22.75 \tabularnewline
77 & 85 & 129.75 & -44.75 \tabularnewline
78 & 155 & 129.75 & 25.25 \tabularnewline
79 & 88 & 65.2125984251968 & 22.7874015748032 \tabularnewline
80 & 155 & 109.942857142857 & 45.0571428571429 \tabularnewline
81 & 104 & 109.942857142857 & -5.94285714285714 \tabularnewline
82 & 132 & 129.75 & 2.25 \tabularnewline
83 & 127 & 129.75 & -2.75 \tabularnewline
84 & 108 & 129.75 & -21.75 \tabularnewline
85 & 129 & 109.942857142857 & 19.0571428571429 \tabularnewline
86 & 116 & 129.75 & -13.75 \tabularnewline
87 & 122 & 109.942857142857 & 12.0571428571429 \tabularnewline
88 & 85 & 65.2125984251968 & 19.7874015748032 \tabularnewline
89 & 147 & 129.75 & 17.25 \tabularnewline
90 & 99 & 99.6666666666667 & -0.666666666666671 \tabularnewline
91 & 87 & 129.75 & -42.75 \tabularnewline
92 & 28 & 65.2125984251968 & -37.2125984251968 \tabularnewline
93 & 90 & 65.2125984251968 & 24.7874015748032 \tabularnewline
94 & 109 & 109.942857142857 & -0.942857142857136 \tabularnewline
95 & 78 & 65.2125984251968 & 12.7874015748032 \tabularnewline
96 & 111 & 109.942857142857 & 1.05714285714286 \tabularnewline
97 & 158 & 129.75 & 28.25 \tabularnewline
98 & 141 & 129.75 & 11.25 \tabularnewline
99 & 122 & 109.942857142857 & 12.0571428571429 \tabularnewline
100 & 124 & 129.75 & -5.75 \tabularnewline
101 & 93 & 99.6666666666667 & -6.66666666666667 \tabularnewline
102 & 124 & 129.75 & -5.75 \tabularnewline
103 & 112 & 109.942857142857 & 2.05714285714286 \tabularnewline
104 & 108 & 109.942857142857 & -1.94285714285714 \tabularnewline
105 & 99 & 129.75 & -30.75 \tabularnewline
106 & 117 & 129.75 & -12.75 \tabularnewline
107 & 199 & 129.75 & 69.25 \tabularnewline
108 & 78 & 65.2125984251968 & 12.7874015748032 \tabularnewline
109 & 91 & 129.75 & -38.75 \tabularnewline
110 & 158 & 129.75 & 28.25 \tabularnewline
111 & 126 & 129.75 & -3.75 \tabularnewline
112 & 122 & 99.6666666666667 & 22.3333333333333 \tabularnewline
113 & 71 & 49.9 & 21.1 \tabularnewline
114 & 75 & 109.942857142857 & -34.9428571428571 \tabularnewline
115 & 115 & 129.75 & -14.75 \tabularnewline
116 & 119 & 129.75 & -10.75 \tabularnewline
117 & 124 & 129.75 & -5.75 \tabularnewline
118 & 72 & 99.6666666666667 & -27.6666666666667 \tabularnewline
119 & 91 & 65.2125984251968 & 25.7874015748032 \tabularnewline
120 & 45 & 65.2125984251968 & -20.2125984251968 \tabularnewline
121 & 78 & 109.942857142857 & -31.9428571428571 \tabularnewline
122 & 39 & 65.2125984251968 & -26.2125984251968 \tabularnewline
123 & 68 & 65.2125984251968 & 2.78740157480316 \tabularnewline
124 & 119 & 129.75 & -10.75 \tabularnewline
125 & 117 & 99.6666666666667 & 17.3333333333333 \tabularnewline
126 & 39 & 65.2125984251968 & -26.2125984251968 \tabularnewline
127 & 50 & 65.2125984251968 & -15.2125984251968 \tabularnewline
128 & 88 & 109.942857142857 & -21.9428571428571 \tabularnewline
129 & 155 & 129.75 & 25.25 \tabularnewline
130 & 0 & 11.9375 & -11.9375 \tabularnewline
131 & 36 & 49.9 & -13.9 \tabularnewline
132 & 123 & 129.75 & -6.75 \tabularnewline
133 & 32 & 65.2125984251968 & -33.2125984251968 \tabularnewline
134 & 99 & 65.2125984251968 & 33.7874015748032 \tabularnewline
135 & 136 & 109.942857142857 & 26.0571428571429 \tabularnewline
136 & 117 & 129.75 & -12.75 \tabularnewline
137 & 0 & 11.9375 & -11.9375 \tabularnewline
138 & 88 & 109.942857142857 & -21.9428571428571 \tabularnewline
139 & 39 & 49.9 & -10.9 \tabularnewline
140 & 25 & 11.9375 & 13.0625 \tabularnewline
141 & 52 & 65.2125984251968 & -13.2125984251968 \tabularnewline
142 & 75 & 109.942857142857 & -34.9428571428571 \tabularnewline
143 & 71 & 65.2125984251968 & 5.78740157480316 \tabularnewline
144 & 124 & 129.75 & -5.75 \tabularnewline
145 & 151 & 109.942857142857 & 41.0571428571429 \tabularnewline
146 & 71 & 65.2125984251968 & 5.78740157480316 \tabularnewline
147 & 145 & 65.2125984251968 & 79.7874015748032 \tabularnewline
148 & 87 & 65.2125984251968 & 21.7874015748032 \tabularnewline
149 & 27 & 49.9 & -22.9 \tabularnewline
150 & 131 & 99.6666666666667 & 31.3333333333333 \tabularnewline
151 & 162 & 129.75 & 32.25 \tabularnewline
152 & 165 & 99.6666666666667 & 65.3333333333333 \tabularnewline
153 & 54 & 65.2125984251968 & -11.2125984251968 \tabularnewline
154 & 159 & 129.75 & 29.25 \tabularnewline
155 & 147 & 129.75 & 17.25 \tabularnewline
156 & 170 & 129.75 & 40.25 \tabularnewline
157 & 119 & 109.942857142857 & 9.05714285714286 \tabularnewline
158 & 49 & 65.2125984251968 & -16.2125984251968 \tabularnewline
159 & 104 & 65.2125984251968 & 38.7874015748032 \tabularnewline
160 & 120 & 109.942857142857 & 10.0571428571429 \tabularnewline
161 & 150 & 129.75 & 20.25 \tabularnewline
162 & 112 & 65.2125984251968 & 46.7874015748032 \tabularnewline
163 & 59 & 65.2125984251968 & -6.21259842519684 \tabularnewline
164 & 136 & 129.75 & 6.25 \tabularnewline
165 & 107 & 65.2125984251968 & 41.7874015748032 \tabularnewline
166 & 130 & 129.75 & 0.25 \tabularnewline
167 & 115 & 109.942857142857 & 5.05714285714286 \tabularnewline
168 & 107 & 99.6666666666667 & 7.33333333333333 \tabularnewline
169 & 75 & 65.2125984251968 & 9.78740157480316 \tabularnewline
170 & 71 & 99.6666666666667 & -28.6666666666667 \tabularnewline
171 & 120 & 129.75 & -9.75 \tabularnewline
172 & 116 & 129.75 & -13.75 \tabularnewline
173 & 79 & 99.6666666666667 & -20.6666666666667 \tabularnewline
174 & 150 & 129.75 & 20.25 \tabularnewline
175 & 156 & 129.75 & 26.25 \tabularnewline
176 & 51 & 65.2125984251968 & -14.2125984251968 \tabularnewline
177 & 118 & 129.75 & -11.75 \tabularnewline
178 & 71 & 65.2125984251968 & 5.78740157480316 \tabularnewline
179 & 144 & 129.75 & 14.25 \tabularnewline
180 & 47 & 65.2125984251968 & -18.2125984251968 \tabularnewline
181 & 28 & 65.2125984251968 & -37.2125984251968 \tabularnewline
182 & 68 & 109.942857142857 & -41.9428571428571 \tabularnewline
183 & 0 & 11.9375 & -11.9375 \tabularnewline
184 & 110 & 99.6666666666667 & 10.3333333333333 \tabularnewline
185 & 147 & 129.75 & 17.25 \tabularnewline
186 & 0 & 11.9375 & -11.9375 \tabularnewline
187 & 15 & 65.2125984251968 & -50.2125984251968 \tabularnewline
188 & 4 & 11.9375 & -7.9375 \tabularnewline
189 & 64 & 65.2125984251968 & -1.21259842519684 \tabularnewline
190 & 111 & 65.2125984251968 & 45.7874015748032 \tabularnewline
191 & 85 & 99.6666666666667 & -14.6666666666667 \tabularnewline
192 & 68 & 65.2125984251968 & 2.78740157480316 \tabularnewline
193 & 40 & 65.2125984251968 & -25.2125984251968 \tabularnewline
194 & 80 & 65.2125984251968 & 14.7874015748032 \tabularnewline
195 & 88 & 99.6666666666667 & -11.6666666666667 \tabularnewline
196 & 48 & 65.2125984251968 & -17.2125984251968 \tabularnewline
197 & 76 & 65.2125984251968 & 10.7874015748032 \tabularnewline
198 & 51 & 65.2125984251968 & -14.2125984251968 \tabularnewline
199 & 67 & 65.2125984251968 & 1.78740157480316 \tabularnewline
200 & 59 & 65.2125984251968 & -6.21259842519684 \tabularnewline
201 & 61 & 65.2125984251968 & -4.21259842519684 \tabularnewline
202 & 76 & 65.2125984251968 & 10.7874015748032 \tabularnewline
203 & 60 & 65.2125984251968 & -5.21259842519684 \tabularnewline
204 & 68 & 65.2125984251968 & 2.78740157480316 \tabularnewline
205 & 71 & 65.2125984251968 & 5.78740157480316 \tabularnewline
206 & 76 & 65.2125984251968 & 10.7874015748032 \tabularnewline
207 & 62 & 65.2125984251968 & -3.21259842519684 \tabularnewline
208 & 61 & 99.6666666666667 & -38.6666666666667 \tabularnewline
209 & 67 & 65.2125984251968 & 1.78740157480316 \tabularnewline
210 & 88 & 65.2125984251968 & 22.7874015748032 \tabularnewline
211 & 30 & 65.2125984251968 & -35.2125984251968 \tabularnewline
212 & 64 & 65.2125984251968 & -1.21259842519684 \tabularnewline
213 & 68 & 65.2125984251968 & 2.78740157480316 \tabularnewline
214 & 64 & 65.2125984251968 & -1.21259842519684 \tabularnewline
215 & 91 & 65.2125984251968 & 25.7874015748032 \tabularnewline
216 & 88 & 65.2125984251968 & 22.7874015748032 \tabularnewline
217 & 52 & 65.2125984251968 & -13.2125984251968 \tabularnewline
218 & 49 & 65.2125984251968 & -16.2125984251968 \tabularnewline
219 & 62 & 65.2125984251968 & -3.21259842519684 \tabularnewline
220 & 61 & 65.2125984251968 & -4.21259842519684 \tabularnewline
221 & 76 & 65.2125984251968 & 10.7874015748032 \tabularnewline
222 & 88 & 65.2125984251968 & 22.7874015748032 \tabularnewline
223 & 66 & 109.942857142857 & -43.9428571428571 \tabularnewline
224 & 71 & 65.2125984251968 & 5.78740157480316 \tabularnewline
225 & 68 & 49.9 & 18.1 \tabularnewline
226 & 48 & 65.2125984251968 & -17.2125984251968 \tabularnewline
227 & 25 & 65.2125984251968 & -40.2125984251968 \tabularnewline
228 & 68 & 65.2125984251968 & 2.78740157480316 \tabularnewline
229 & 41 & 65.2125984251968 & -24.2125984251968 \tabularnewline
230 & 90 & 65.2125984251968 & 24.7874015748032 \tabularnewline
231 & 66 & 49.9 & 16.1 \tabularnewline
232 & 54 & 65.2125984251968 & -11.2125984251968 \tabularnewline
233 & 59 & 65.2125984251968 & -6.21259842519684 \tabularnewline
234 & 60 & 65.2125984251968 & -5.21259842519684 \tabularnewline
235 & 77 & 65.2125984251968 & 11.7874015748032 \tabularnewline
236 & 68 & 65.2125984251968 & 2.78740157480316 \tabularnewline
237 & 72 & 99.6666666666667 & -27.6666666666667 \tabularnewline
238 & 67 & 65.2125984251968 & 1.78740157480316 \tabularnewline
239 & 64 & 65.2125984251968 & -1.21259842519684 \tabularnewline
240 & 63 & 49.9 & 13.1 \tabularnewline
241 & 59 & 65.2125984251968 & -6.21259842519684 \tabularnewline
242 & 84 & 99.6666666666667 & -15.6666666666667 \tabularnewline
243 & 64 & 65.2125984251968 & -1.21259842519684 \tabularnewline
244 & 56 & 65.2125984251968 & -9.21259842519684 \tabularnewline
245 & 54 & 65.2125984251968 & -11.2125984251968 \tabularnewline
246 & 67 & 65.2125984251968 & 1.78740157480316 \tabularnewline
247 & 58 & 65.2125984251968 & -7.21259842519684 \tabularnewline
248 & 59 & 65.2125984251968 & -6.21259842519684 \tabularnewline
249 & 40 & 65.2125984251968 & -25.2125984251968 \tabularnewline
250 & 22 & 11.9375 & 10.0625 \tabularnewline
251 & 83 & 99.6666666666667 & -16.6666666666667 \tabularnewline
252 & 81 & 65.2125984251968 & 15.7874015748032 \tabularnewline
253 & 2 & 11.9375 & -9.9375 \tabularnewline
254 & 72 & 65.2125984251968 & 6.78740157480316 \tabularnewline
255 & 61 & 65.2125984251968 & -4.21259842519684 \tabularnewline
256 & 15 & 11.9375 & 3.0625 \tabularnewline
257 & 32 & 11.9375 & 20.0625 \tabularnewline
258 & 62 & 65.2125984251968 & -3.21259842519684 \tabularnewline
259 & 58 & 65.2125984251968 & -7.21259842519684 \tabularnewline
260 & 36 & 11.9375 & 24.0625 \tabularnewline
261 & 59 & 49.9 & 9.1 \tabularnewline
262 & 68 & 65.2125984251968 & 2.78740157480316 \tabularnewline
263 & 21 & 11.9375 & 9.0625 \tabularnewline
264 & 55 & 65.2125984251968 & -10.2125984251968 \tabularnewline
265 & 54 & 65.2125984251968 & -11.2125984251968 \tabularnewline
266 & 55 & 65.2125984251968 & -10.2125984251968 \tabularnewline
267 & 72 & 65.2125984251968 & 6.78740157480316 \tabularnewline
268 & 41 & 65.2125984251968 & -24.2125984251968 \tabularnewline
269 & 61 & 65.2125984251968 & -4.21259842519684 \tabularnewline
270 & 67 & 65.2125984251968 & 1.78740157480316 \tabularnewline
271 & 76 & 65.2125984251968 & 10.7874015748032 \tabularnewline
272 & 64 & 65.2125984251968 & -1.21259842519684 \tabularnewline
273 & 3 & 49.9 & -46.9 \tabularnewline
274 & 63 & 65.2125984251968 & -2.21259842519684 \tabularnewline
275 & 40 & 65.2125984251968 & -25.2125984251968 \tabularnewline
276 & 69 & 65.2125984251968 & 3.78740157480316 \tabularnewline
277 & 48 & 65.2125984251968 & -17.2125984251968 \tabularnewline
278 & 8 & 11.9375 & -3.9375 \tabularnewline
279 & 52 & 65.2125984251968 & -13.2125984251968 \tabularnewline
280 & 66 & 65.2125984251968 & 0.787401574803155 \tabularnewline
281 & 76 & 65.2125984251968 & 10.7874015748032 \tabularnewline
282 & 43 & 65.2125984251968 & -22.2125984251968 \tabularnewline
283 & 39 & 65.2125984251968 & -26.2125984251968 \tabularnewline
284 & 14 & 11.9375 & 2.0625 \tabularnewline
285 & 61 & 65.2125984251968 & -4.21259842519684 \tabularnewline
286 & 71 & 65.2125984251968 & 5.78740157480316 \tabularnewline
287 & 44 & 65.2125984251968 & -21.2125984251968 \tabularnewline
288 & 60 & 65.2125984251968 & -5.21259842519684 \tabularnewline
289 & 64 & 65.2125984251968 & -1.21259842519684 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=158821&T=2

[TABLE]
[ROW][C]Actuals, Predictions, and Residuals[/C][/ROW]
[ROW][C]#[/C][C]Actuals[/C][C]Forecasts[/C][C]Residuals[/C][/ROW]
[ROW][C]1[/C][C]115[/C][C]129.75[/C][C]-14.75[/C][/ROW]
[ROW][C]2[/C][C]109[/C][C]109.942857142857[/C][C]-0.942857142857136[/C][/ROW]
[ROW][C]3[/C][C]146[/C][C]109.942857142857[/C][C]36.0571428571429[/C][/ROW]
[ROW][C]4[/C][C]116[/C][C]129.75[/C][C]-13.75[/C][/ROW]
[ROW][C]5[/C][C]68[/C][C]65.2125984251968[/C][C]2.78740157480316[/C][/ROW]
[ROW][C]6[/C][C]101[/C][C]65.2125984251968[/C][C]35.7874015748032[/C][/ROW]
[ROW][C]7[/C][C]96[/C][C]129.75[/C][C]-33.75[/C][/ROW]
[ROW][C]8[/C][C]67[/C][C]49.9[/C][C]17.1[/C][/ROW]
[ROW][C]9[/C][C]44[/C][C]65.2125984251968[/C][C]-21.2125984251968[/C][/ROW]
[ROW][C]10[/C][C]100[/C][C]99.6666666666667[/C][C]0.333333333333329[/C][/ROW]
[ROW][C]11[/C][C]93[/C][C]109.942857142857[/C][C]-16.9428571428571[/C][/ROW]
[ROW][C]12[/C][C]140[/C][C]129.75[/C][C]10.25[/C][/ROW]
[ROW][C]13[/C][C]166[/C][C]129.75[/C][C]36.25[/C][/ROW]
[ROW][C]14[/C][C]99[/C][C]65.2125984251968[/C][C]33.7874015748032[/C][/ROW]
[ROW][C]15[/C][C]139[/C][C]129.75[/C][C]9.25[/C][/ROW]
[ROW][C]16[/C][C]130[/C][C]109.942857142857[/C][C]20.0571428571429[/C][/ROW]
[ROW][C]17[/C][C]181[/C][C]129.75[/C][C]51.25[/C][/ROW]
[ROW][C]18[/C][C]116[/C][C]129.75[/C][C]-13.75[/C][/ROW]
[ROW][C]19[/C][C]116[/C][C]129.75[/C][C]-13.75[/C][/ROW]
[ROW][C]20[/C][C]88[/C][C]129.75[/C][C]-41.75[/C][/ROW]
[ROW][C]21[/C][C]139[/C][C]129.75[/C][C]9.25[/C][/ROW]
[ROW][C]22[/C][C]135[/C][C]129.75[/C][C]5.25[/C][/ROW]
[ROW][C]23[/C][C]108[/C][C]129.75[/C][C]-21.75[/C][/ROW]
[ROW][C]24[/C][C]89[/C][C]99.6666666666667[/C][C]-10.6666666666667[/C][/ROW]
[ROW][C]25[/C][C]156[/C][C]129.75[/C][C]26.25[/C][/ROW]
[ROW][C]26[/C][C]129[/C][C]129.75[/C][C]-0.75[/C][/ROW]
[ROW][C]27[/C][C]118[/C][C]109.942857142857[/C][C]8.05714285714286[/C][/ROW]
[ROW][C]28[/C][C]118[/C][C]129.75[/C][C]-11.75[/C][/ROW]
[ROW][C]29[/C][C]125[/C][C]129.75[/C][C]-4.75[/C][/ROW]
[ROW][C]30[/C][C]95[/C][C]65.2125984251968[/C][C]29.7874015748032[/C][/ROW]
[ROW][C]31[/C][C]126[/C][C]129.75[/C][C]-3.75[/C][/ROW]
[ROW][C]32[/C][C]135[/C][C]129.75[/C][C]5.25[/C][/ROW]
[ROW][C]33[/C][C]154[/C][C]99.6666666666667[/C][C]54.3333333333333[/C][/ROW]
[ROW][C]34[/C][C]165[/C][C]129.75[/C][C]35.25[/C][/ROW]
[ROW][C]35[/C][C]113[/C][C]65.2125984251968[/C][C]47.7874015748032[/C][/ROW]
[ROW][C]36[/C][C]127[/C][C]129.75[/C][C]-2.75[/C][/ROW]
[ROW][C]37[/C][C]52[/C][C]65.2125984251968[/C][C]-13.2125984251968[/C][/ROW]
[ROW][C]38[/C][C]121[/C][C]109.942857142857[/C][C]11.0571428571429[/C][/ROW]
[ROW][C]39[/C][C]136[/C][C]129.75[/C][C]6.25[/C][/ROW]
[ROW][C]40[/C][C]0[/C][C]11.9375[/C][C]-11.9375[/C][/ROW]
[ROW][C]41[/C][C]108[/C][C]109.942857142857[/C][C]-1.94285714285714[/C][/ROW]
[ROW][C]42[/C][C]46[/C][C]65.2125984251968[/C][C]-19.2125984251968[/C][/ROW]
[ROW][C]43[/C][C]54[/C][C]65.2125984251968[/C][C]-11.2125984251968[/C][/ROW]
[ROW][C]44[/C][C]124[/C][C]129.75[/C][C]-5.75[/C][/ROW]
[ROW][C]45[/C][C]115[/C][C]129.75[/C][C]-14.75[/C][/ROW]
[ROW][C]46[/C][C]128[/C][C]109.942857142857[/C][C]18.0571428571429[/C][/ROW]
[ROW][C]47[/C][C]80[/C][C]109.942857142857[/C][C]-29.9428571428571[/C][/ROW]
[ROW][C]48[/C][C]97[/C][C]109.942857142857[/C][C]-12.9428571428571[/C][/ROW]
[ROW][C]49[/C][C]104[/C][C]65.2125984251968[/C][C]38.7874015748032[/C][/ROW]
[ROW][C]50[/C][C]59[/C][C]65.2125984251968[/C][C]-6.21259842519684[/C][/ROW]
[ROW][C]51[/C][C]125[/C][C]129.75[/C][C]-4.75[/C][/ROW]
[ROW][C]52[/C][C]82[/C][C]65.2125984251968[/C][C]16.7874015748032[/C][/ROW]
[ROW][C]53[/C][C]149[/C][C]129.75[/C][C]19.25[/C][/ROW]
[ROW][C]54[/C][C]149[/C][C]129.75[/C][C]19.25[/C][/ROW]
[ROW][C]55[/C][C]122[/C][C]129.75[/C][C]-7.75[/C][/ROW]
[ROW][C]56[/C][C]118[/C][C]129.75[/C][C]-11.75[/C][/ROW]
[ROW][C]57[/C][C]12[/C][C]11.9375[/C][C]0.0625[/C][/ROW]
[ROW][C]58[/C][C]144[/C][C]129.75[/C][C]14.25[/C][/ROW]
[ROW][C]59[/C][C]67[/C][C]65.2125984251968[/C][C]1.78740157480316[/C][/ROW]
[ROW][C]60[/C][C]52[/C][C]65.2125984251968[/C][C]-13.2125984251968[/C][/ROW]
[ROW][C]61[/C][C]108[/C][C]129.75[/C][C]-21.75[/C][/ROW]
[ROW][C]62[/C][C]166[/C][C]129.75[/C][C]36.25[/C][/ROW]
[ROW][C]63[/C][C]80[/C][C]129.75[/C][C]-49.75[/C][/ROW]
[ROW][C]64[/C][C]60[/C][C]65.2125984251968[/C][C]-5.21259842519684[/C][/ROW]
[ROW][C]65[/C][C]107[/C][C]129.75[/C][C]-22.75[/C][/ROW]
[ROW][C]66[/C][C]127[/C][C]129.75[/C][C]-2.75[/C][/ROW]
[ROW][C]67[/C][C]107[/C][C]129.75[/C][C]-22.75[/C][/ROW]
[ROW][C]68[/C][C]146[/C][C]129.75[/C][C]16.25[/C][/ROW]
[ROW][C]69[/C][C]84[/C][C]129.75[/C][C]-45.75[/C][/ROW]
[ROW][C]70[/C][C]141[/C][C]109.942857142857[/C][C]31.0571428571429[/C][/ROW]
[ROW][C]71[/C][C]123[/C][C]109.942857142857[/C][C]13.0571428571429[/C][/ROW]
[ROW][C]72[/C][C]111[/C][C]99.6666666666667[/C][C]11.3333333333333[/C][/ROW]
[ROW][C]73[/C][C]98[/C][C]109.942857142857[/C][C]-11.9428571428571[/C][/ROW]
[ROW][C]74[/C][C]105[/C][C]109.942857142857[/C][C]-4.94285714285714[/C][/ROW]
[ROW][C]75[/C][C]135[/C][C]129.75[/C][C]5.25[/C][/ROW]
[ROW][C]76[/C][C]107[/C][C]129.75[/C][C]-22.75[/C][/ROW]
[ROW][C]77[/C][C]85[/C][C]129.75[/C][C]-44.75[/C][/ROW]
[ROW][C]78[/C][C]155[/C][C]129.75[/C][C]25.25[/C][/ROW]
[ROW][C]79[/C][C]88[/C][C]65.2125984251968[/C][C]22.7874015748032[/C][/ROW]
[ROW][C]80[/C][C]155[/C][C]109.942857142857[/C][C]45.0571428571429[/C][/ROW]
[ROW][C]81[/C][C]104[/C][C]109.942857142857[/C][C]-5.94285714285714[/C][/ROW]
[ROW][C]82[/C][C]132[/C][C]129.75[/C][C]2.25[/C][/ROW]
[ROW][C]83[/C][C]127[/C][C]129.75[/C][C]-2.75[/C][/ROW]
[ROW][C]84[/C][C]108[/C][C]129.75[/C][C]-21.75[/C][/ROW]
[ROW][C]85[/C][C]129[/C][C]109.942857142857[/C][C]19.0571428571429[/C][/ROW]
[ROW][C]86[/C][C]116[/C][C]129.75[/C][C]-13.75[/C][/ROW]
[ROW][C]87[/C][C]122[/C][C]109.942857142857[/C][C]12.0571428571429[/C][/ROW]
[ROW][C]88[/C][C]85[/C][C]65.2125984251968[/C][C]19.7874015748032[/C][/ROW]
[ROW][C]89[/C][C]147[/C][C]129.75[/C][C]17.25[/C][/ROW]
[ROW][C]90[/C][C]99[/C][C]99.6666666666667[/C][C]-0.666666666666671[/C][/ROW]
[ROW][C]91[/C][C]87[/C][C]129.75[/C][C]-42.75[/C][/ROW]
[ROW][C]92[/C][C]28[/C][C]65.2125984251968[/C][C]-37.2125984251968[/C][/ROW]
[ROW][C]93[/C][C]90[/C][C]65.2125984251968[/C][C]24.7874015748032[/C][/ROW]
[ROW][C]94[/C][C]109[/C][C]109.942857142857[/C][C]-0.942857142857136[/C][/ROW]
[ROW][C]95[/C][C]78[/C][C]65.2125984251968[/C][C]12.7874015748032[/C][/ROW]
[ROW][C]96[/C][C]111[/C][C]109.942857142857[/C][C]1.05714285714286[/C][/ROW]
[ROW][C]97[/C][C]158[/C][C]129.75[/C][C]28.25[/C][/ROW]
[ROW][C]98[/C][C]141[/C][C]129.75[/C][C]11.25[/C][/ROW]
[ROW][C]99[/C][C]122[/C][C]109.942857142857[/C][C]12.0571428571429[/C][/ROW]
[ROW][C]100[/C][C]124[/C][C]129.75[/C][C]-5.75[/C][/ROW]
[ROW][C]101[/C][C]93[/C][C]99.6666666666667[/C][C]-6.66666666666667[/C][/ROW]
[ROW][C]102[/C][C]124[/C][C]129.75[/C][C]-5.75[/C][/ROW]
[ROW][C]103[/C][C]112[/C][C]109.942857142857[/C][C]2.05714285714286[/C][/ROW]
[ROW][C]104[/C][C]108[/C][C]109.942857142857[/C][C]-1.94285714285714[/C][/ROW]
[ROW][C]105[/C][C]99[/C][C]129.75[/C][C]-30.75[/C][/ROW]
[ROW][C]106[/C][C]117[/C][C]129.75[/C][C]-12.75[/C][/ROW]
[ROW][C]107[/C][C]199[/C][C]129.75[/C][C]69.25[/C][/ROW]
[ROW][C]108[/C][C]78[/C][C]65.2125984251968[/C][C]12.7874015748032[/C][/ROW]
[ROW][C]109[/C][C]91[/C][C]129.75[/C][C]-38.75[/C][/ROW]
[ROW][C]110[/C][C]158[/C][C]129.75[/C][C]28.25[/C][/ROW]
[ROW][C]111[/C][C]126[/C][C]129.75[/C][C]-3.75[/C][/ROW]
[ROW][C]112[/C][C]122[/C][C]99.6666666666667[/C][C]22.3333333333333[/C][/ROW]
[ROW][C]113[/C][C]71[/C][C]49.9[/C][C]21.1[/C][/ROW]
[ROW][C]114[/C][C]75[/C][C]109.942857142857[/C][C]-34.9428571428571[/C][/ROW]
[ROW][C]115[/C][C]115[/C][C]129.75[/C][C]-14.75[/C][/ROW]
[ROW][C]116[/C][C]119[/C][C]129.75[/C][C]-10.75[/C][/ROW]
[ROW][C]117[/C][C]124[/C][C]129.75[/C][C]-5.75[/C][/ROW]
[ROW][C]118[/C][C]72[/C][C]99.6666666666667[/C][C]-27.6666666666667[/C][/ROW]
[ROW][C]119[/C][C]91[/C][C]65.2125984251968[/C][C]25.7874015748032[/C][/ROW]
[ROW][C]120[/C][C]45[/C][C]65.2125984251968[/C][C]-20.2125984251968[/C][/ROW]
[ROW][C]121[/C][C]78[/C][C]109.942857142857[/C][C]-31.9428571428571[/C][/ROW]
[ROW][C]122[/C][C]39[/C][C]65.2125984251968[/C][C]-26.2125984251968[/C][/ROW]
[ROW][C]123[/C][C]68[/C][C]65.2125984251968[/C][C]2.78740157480316[/C][/ROW]
[ROW][C]124[/C][C]119[/C][C]129.75[/C][C]-10.75[/C][/ROW]
[ROW][C]125[/C][C]117[/C][C]99.6666666666667[/C][C]17.3333333333333[/C][/ROW]
[ROW][C]126[/C][C]39[/C][C]65.2125984251968[/C][C]-26.2125984251968[/C][/ROW]
[ROW][C]127[/C][C]50[/C][C]65.2125984251968[/C][C]-15.2125984251968[/C][/ROW]
[ROW][C]128[/C][C]88[/C][C]109.942857142857[/C][C]-21.9428571428571[/C][/ROW]
[ROW][C]129[/C][C]155[/C][C]129.75[/C][C]25.25[/C][/ROW]
[ROW][C]130[/C][C]0[/C][C]11.9375[/C][C]-11.9375[/C][/ROW]
[ROW][C]131[/C][C]36[/C][C]49.9[/C][C]-13.9[/C][/ROW]
[ROW][C]132[/C][C]123[/C][C]129.75[/C][C]-6.75[/C][/ROW]
[ROW][C]133[/C][C]32[/C][C]65.2125984251968[/C][C]-33.2125984251968[/C][/ROW]
[ROW][C]134[/C][C]99[/C][C]65.2125984251968[/C][C]33.7874015748032[/C][/ROW]
[ROW][C]135[/C][C]136[/C][C]109.942857142857[/C][C]26.0571428571429[/C][/ROW]
[ROW][C]136[/C][C]117[/C][C]129.75[/C][C]-12.75[/C][/ROW]
[ROW][C]137[/C][C]0[/C][C]11.9375[/C][C]-11.9375[/C][/ROW]
[ROW][C]138[/C][C]88[/C][C]109.942857142857[/C][C]-21.9428571428571[/C][/ROW]
[ROW][C]139[/C][C]39[/C][C]49.9[/C][C]-10.9[/C][/ROW]
[ROW][C]140[/C][C]25[/C][C]11.9375[/C][C]13.0625[/C][/ROW]
[ROW][C]141[/C][C]52[/C][C]65.2125984251968[/C][C]-13.2125984251968[/C][/ROW]
[ROW][C]142[/C][C]75[/C][C]109.942857142857[/C][C]-34.9428571428571[/C][/ROW]
[ROW][C]143[/C][C]71[/C][C]65.2125984251968[/C][C]5.78740157480316[/C][/ROW]
[ROW][C]144[/C][C]124[/C][C]129.75[/C][C]-5.75[/C][/ROW]
[ROW][C]145[/C][C]151[/C][C]109.942857142857[/C][C]41.0571428571429[/C][/ROW]
[ROW][C]146[/C][C]71[/C][C]65.2125984251968[/C][C]5.78740157480316[/C][/ROW]
[ROW][C]147[/C][C]145[/C][C]65.2125984251968[/C][C]79.7874015748032[/C][/ROW]
[ROW][C]148[/C][C]87[/C][C]65.2125984251968[/C][C]21.7874015748032[/C][/ROW]
[ROW][C]149[/C][C]27[/C][C]49.9[/C][C]-22.9[/C][/ROW]
[ROW][C]150[/C][C]131[/C][C]99.6666666666667[/C][C]31.3333333333333[/C][/ROW]
[ROW][C]151[/C][C]162[/C][C]129.75[/C][C]32.25[/C][/ROW]
[ROW][C]152[/C][C]165[/C][C]99.6666666666667[/C][C]65.3333333333333[/C][/ROW]
[ROW][C]153[/C][C]54[/C][C]65.2125984251968[/C][C]-11.2125984251968[/C][/ROW]
[ROW][C]154[/C][C]159[/C][C]129.75[/C][C]29.25[/C][/ROW]
[ROW][C]155[/C][C]147[/C][C]129.75[/C][C]17.25[/C][/ROW]
[ROW][C]156[/C][C]170[/C][C]129.75[/C][C]40.25[/C][/ROW]
[ROW][C]157[/C][C]119[/C][C]109.942857142857[/C][C]9.05714285714286[/C][/ROW]
[ROW][C]158[/C][C]49[/C][C]65.2125984251968[/C][C]-16.2125984251968[/C][/ROW]
[ROW][C]159[/C][C]104[/C][C]65.2125984251968[/C][C]38.7874015748032[/C][/ROW]
[ROW][C]160[/C][C]120[/C][C]109.942857142857[/C][C]10.0571428571429[/C][/ROW]
[ROW][C]161[/C][C]150[/C][C]129.75[/C][C]20.25[/C][/ROW]
[ROW][C]162[/C][C]112[/C][C]65.2125984251968[/C][C]46.7874015748032[/C][/ROW]
[ROW][C]163[/C][C]59[/C][C]65.2125984251968[/C][C]-6.21259842519684[/C][/ROW]
[ROW][C]164[/C][C]136[/C][C]129.75[/C][C]6.25[/C][/ROW]
[ROW][C]165[/C][C]107[/C][C]65.2125984251968[/C][C]41.7874015748032[/C][/ROW]
[ROW][C]166[/C][C]130[/C][C]129.75[/C][C]0.25[/C][/ROW]
[ROW][C]167[/C][C]115[/C][C]109.942857142857[/C][C]5.05714285714286[/C][/ROW]
[ROW][C]168[/C][C]107[/C][C]99.6666666666667[/C][C]7.33333333333333[/C][/ROW]
[ROW][C]169[/C][C]75[/C][C]65.2125984251968[/C][C]9.78740157480316[/C][/ROW]
[ROW][C]170[/C][C]71[/C][C]99.6666666666667[/C][C]-28.6666666666667[/C][/ROW]
[ROW][C]171[/C][C]120[/C][C]129.75[/C][C]-9.75[/C][/ROW]
[ROW][C]172[/C][C]116[/C][C]129.75[/C][C]-13.75[/C][/ROW]
[ROW][C]173[/C][C]79[/C][C]99.6666666666667[/C][C]-20.6666666666667[/C][/ROW]
[ROW][C]174[/C][C]150[/C][C]129.75[/C][C]20.25[/C][/ROW]
[ROW][C]175[/C][C]156[/C][C]129.75[/C][C]26.25[/C][/ROW]
[ROW][C]176[/C][C]51[/C][C]65.2125984251968[/C][C]-14.2125984251968[/C][/ROW]
[ROW][C]177[/C][C]118[/C][C]129.75[/C][C]-11.75[/C][/ROW]
[ROW][C]178[/C][C]71[/C][C]65.2125984251968[/C][C]5.78740157480316[/C][/ROW]
[ROW][C]179[/C][C]144[/C][C]129.75[/C][C]14.25[/C][/ROW]
[ROW][C]180[/C][C]47[/C][C]65.2125984251968[/C][C]-18.2125984251968[/C][/ROW]
[ROW][C]181[/C][C]28[/C][C]65.2125984251968[/C][C]-37.2125984251968[/C][/ROW]
[ROW][C]182[/C][C]68[/C][C]109.942857142857[/C][C]-41.9428571428571[/C][/ROW]
[ROW][C]183[/C][C]0[/C][C]11.9375[/C][C]-11.9375[/C][/ROW]
[ROW][C]184[/C][C]110[/C][C]99.6666666666667[/C][C]10.3333333333333[/C][/ROW]
[ROW][C]185[/C][C]147[/C][C]129.75[/C][C]17.25[/C][/ROW]
[ROW][C]186[/C][C]0[/C][C]11.9375[/C][C]-11.9375[/C][/ROW]
[ROW][C]187[/C][C]15[/C][C]65.2125984251968[/C][C]-50.2125984251968[/C][/ROW]
[ROW][C]188[/C][C]4[/C][C]11.9375[/C][C]-7.9375[/C][/ROW]
[ROW][C]189[/C][C]64[/C][C]65.2125984251968[/C][C]-1.21259842519684[/C][/ROW]
[ROW][C]190[/C][C]111[/C][C]65.2125984251968[/C][C]45.7874015748032[/C][/ROW]
[ROW][C]191[/C][C]85[/C][C]99.6666666666667[/C][C]-14.6666666666667[/C][/ROW]
[ROW][C]192[/C][C]68[/C][C]65.2125984251968[/C][C]2.78740157480316[/C][/ROW]
[ROW][C]193[/C][C]40[/C][C]65.2125984251968[/C][C]-25.2125984251968[/C][/ROW]
[ROW][C]194[/C][C]80[/C][C]65.2125984251968[/C][C]14.7874015748032[/C][/ROW]
[ROW][C]195[/C][C]88[/C][C]99.6666666666667[/C][C]-11.6666666666667[/C][/ROW]
[ROW][C]196[/C][C]48[/C][C]65.2125984251968[/C][C]-17.2125984251968[/C][/ROW]
[ROW][C]197[/C][C]76[/C][C]65.2125984251968[/C][C]10.7874015748032[/C][/ROW]
[ROW][C]198[/C][C]51[/C][C]65.2125984251968[/C][C]-14.2125984251968[/C][/ROW]
[ROW][C]199[/C][C]67[/C][C]65.2125984251968[/C][C]1.78740157480316[/C][/ROW]
[ROW][C]200[/C][C]59[/C][C]65.2125984251968[/C][C]-6.21259842519684[/C][/ROW]
[ROW][C]201[/C][C]61[/C][C]65.2125984251968[/C][C]-4.21259842519684[/C][/ROW]
[ROW][C]202[/C][C]76[/C][C]65.2125984251968[/C][C]10.7874015748032[/C][/ROW]
[ROW][C]203[/C][C]60[/C][C]65.2125984251968[/C][C]-5.21259842519684[/C][/ROW]
[ROW][C]204[/C][C]68[/C][C]65.2125984251968[/C][C]2.78740157480316[/C][/ROW]
[ROW][C]205[/C][C]71[/C][C]65.2125984251968[/C][C]5.78740157480316[/C][/ROW]
[ROW][C]206[/C][C]76[/C][C]65.2125984251968[/C][C]10.7874015748032[/C][/ROW]
[ROW][C]207[/C][C]62[/C][C]65.2125984251968[/C][C]-3.21259842519684[/C][/ROW]
[ROW][C]208[/C][C]61[/C][C]99.6666666666667[/C][C]-38.6666666666667[/C][/ROW]
[ROW][C]209[/C][C]67[/C][C]65.2125984251968[/C][C]1.78740157480316[/C][/ROW]
[ROW][C]210[/C][C]88[/C][C]65.2125984251968[/C][C]22.7874015748032[/C][/ROW]
[ROW][C]211[/C][C]30[/C][C]65.2125984251968[/C][C]-35.2125984251968[/C][/ROW]
[ROW][C]212[/C][C]64[/C][C]65.2125984251968[/C][C]-1.21259842519684[/C][/ROW]
[ROW][C]213[/C][C]68[/C][C]65.2125984251968[/C][C]2.78740157480316[/C][/ROW]
[ROW][C]214[/C][C]64[/C][C]65.2125984251968[/C][C]-1.21259842519684[/C][/ROW]
[ROW][C]215[/C][C]91[/C][C]65.2125984251968[/C][C]25.7874015748032[/C][/ROW]
[ROW][C]216[/C][C]88[/C][C]65.2125984251968[/C][C]22.7874015748032[/C][/ROW]
[ROW][C]217[/C][C]52[/C][C]65.2125984251968[/C][C]-13.2125984251968[/C][/ROW]
[ROW][C]218[/C][C]49[/C][C]65.2125984251968[/C][C]-16.2125984251968[/C][/ROW]
[ROW][C]219[/C][C]62[/C][C]65.2125984251968[/C][C]-3.21259842519684[/C][/ROW]
[ROW][C]220[/C][C]61[/C][C]65.2125984251968[/C][C]-4.21259842519684[/C][/ROW]
[ROW][C]221[/C][C]76[/C][C]65.2125984251968[/C][C]10.7874015748032[/C][/ROW]
[ROW][C]222[/C][C]88[/C][C]65.2125984251968[/C][C]22.7874015748032[/C][/ROW]
[ROW][C]223[/C][C]66[/C][C]109.942857142857[/C][C]-43.9428571428571[/C][/ROW]
[ROW][C]224[/C][C]71[/C][C]65.2125984251968[/C][C]5.78740157480316[/C][/ROW]
[ROW][C]225[/C][C]68[/C][C]49.9[/C][C]18.1[/C][/ROW]
[ROW][C]226[/C][C]48[/C][C]65.2125984251968[/C][C]-17.2125984251968[/C][/ROW]
[ROW][C]227[/C][C]25[/C][C]65.2125984251968[/C][C]-40.2125984251968[/C][/ROW]
[ROW][C]228[/C][C]68[/C][C]65.2125984251968[/C][C]2.78740157480316[/C][/ROW]
[ROW][C]229[/C][C]41[/C][C]65.2125984251968[/C][C]-24.2125984251968[/C][/ROW]
[ROW][C]230[/C][C]90[/C][C]65.2125984251968[/C][C]24.7874015748032[/C][/ROW]
[ROW][C]231[/C][C]66[/C][C]49.9[/C][C]16.1[/C][/ROW]
[ROW][C]232[/C][C]54[/C][C]65.2125984251968[/C][C]-11.2125984251968[/C][/ROW]
[ROW][C]233[/C][C]59[/C][C]65.2125984251968[/C][C]-6.21259842519684[/C][/ROW]
[ROW][C]234[/C][C]60[/C][C]65.2125984251968[/C][C]-5.21259842519684[/C][/ROW]
[ROW][C]235[/C][C]77[/C][C]65.2125984251968[/C][C]11.7874015748032[/C][/ROW]
[ROW][C]236[/C][C]68[/C][C]65.2125984251968[/C][C]2.78740157480316[/C][/ROW]
[ROW][C]237[/C][C]72[/C][C]99.6666666666667[/C][C]-27.6666666666667[/C][/ROW]
[ROW][C]238[/C][C]67[/C][C]65.2125984251968[/C][C]1.78740157480316[/C][/ROW]
[ROW][C]239[/C][C]64[/C][C]65.2125984251968[/C][C]-1.21259842519684[/C][/ROW]
[ROW][C]240[/C][C]63[/C][C]49.9[/C][C]13.1[/C][/ROW]
[ROW][C]241[/C][C]59[/C][C]65.2125984251968[/C][C]-6.21259842519684[/C][/ROW]
[ROW][C]242[/C][C]84[/C][C]99.6666666666667[/C][C]-15.6666666666667[/C][/ROW]
[ROW][C]243[/C][C]64[/C][C]65.2125984251968[/C][C]-1.21259842519684[/C][/ROW]
[ROW][C]244[/C][C]56[/C][C]65.2125984251968[/C][C]-9.21259842519684[/C][/ROW]
[ROW][C]245[/C][C]54[/C][C]65.2125984251968[/C][C]-11.2125984251968[/C][/ROW]
[ROW][C]246[/C][C]67[/C][C]65.2125984251968[/C][C]1.78740157480316[/C][/ROW]
[ROW][C]247[/C][C]58[/C][C]65.2125984251968[/C][C]-7.21259842519684[/C][/ROW]
[ROW][C]248[/C][C]59[/C][C]65.2125984251968[/C][C]-6.21259842519684[/C][/ROW]
[ROW][C]249[/C][C]40[/C][C]65.2125984251968[/C][C]-25.2125984251968[/C][/ROW]
[ROW][C]250[/C][C]22[/C][C]11.9375[/C][C]10.0625[/C][/ROW]
[ROW][C]251[/C][C]83[/C][C]99.6666666666667[/C][C]-16.6666666666667[/C][/ROW]
[ROW][C]252[/C][C]81[/C][C]65.2125984251968[/C][C]15.7874015748032[/C][/ROW]
[ROW][C]253[/C][C]2[/C][C]11.9375[/C][C]-9.9375[/C][/ROW]
[ROW][C]254[/C][C]72[/C][C]65.2125984251968[/C][C]6.78740157480316[/C][/ROW]
[ROW][C]255[/C][C]61[/C][C]65.2125984251968[/C][C]-4.21259842519684[/C][/ROW]
[ROW][C]256[/C][C]15[/C][C]11.9375[/C][C]3.0625[/C][/ROW]
[ROW][C]257[/C][C]32[/C][C]11.9375[/C][C]20.0625[/C][/ROW]
[ROW][C]258[/C][C]62[/C][C]65.2125984251968[/C][C]-3.21259842519684[/C][/ROW]
[ROW][C]259[/C][C]58[/C][C]65.2125984251968[/C][C]-7.21259842519684[/C][/ROW]
[ROW][C]260[/C][C]36[/C][C]11.9375[/C][C]24.0625[/C][/ROW]
[ROW][C]261[/C][C]59[/C][C]49.9[/C][C]9.1[/C][/ROW]
[ROW][C]262[/C][C]68[/C][C]65.2125984251968[/C][C]2.78740157480316[/C][/ROW]
[ROW][C]263[/C][C]21[/C][C]11.9375[/C][C]9.0625[/C][/ROW]
[ROW][C]264[/C][C]55[/C][C]65.2125984251968[/C][C]-10.2125984251968[/C][/ROW]
[ROW][C]265[/C][C]54[/C][C]65.2125984251968[/C][C]-11.2125984251968[/C][/ROW]
[ROW][C]266[/C][C]55[/C][C]65.2125984251968[/C][C]-10.2125984251968[/C][/ROW]
[ROW][C]267[/C][C]72[/C][C]65.2125984251968[/C][C]6.78740157480316[/C][/ROW]
[ROW][C]268[/C][C]41[/C][C]65.2125984251968[/C][C]-24.2125984251968[/C][/ROW]
[ROW][C]269[/C][C]61[/C][C]65.2125984251968[/C][C]-4.21259842519684[/C][/ROW]
[ROW][C]270[/C][C]67[/C][C]65.2125984251968[/C][C]1.78740157480316[/C][/ROW]
[ROW][C]271[/C][C]76[/C][C]65.2125984251968[/C][C]10.7874015748032[/C][/ROW]
[ROW][C]272[/C][C]64[/C][C]65.2125984251968[/C][C]-1.21259842519684[/C][/ROW]
[ROW][C]273[/C][C]3[/C][C]49.9[/C][C]-46.9[/C][/ROW]
[ROW][C]274[/C][C]63[/C][C]65.2125984251968[/C][C]-2.21259842519684[/C][/ROW]
[ROW][C]275[/C][C]40[/C][C]65.2125984251968[/C][C]-25.2125984251968[/C][/ROW]
[ROW][C]276[/C][C]69[/C][C]65.2125984251968[/C][C]3.78740157480316[/C][/ROW]
[ROW][C]277[/C][C]48[/C][C]65.2125984251968[/C][C]-17.2125984251968[/C][/ROW]
[ROW][C]278[/C][C]8[/C][C]11.9375[/C][C]-3.9375[/C][/ROW]
[ROW][C]279[/C][C]52[/C][C]65.2125984251968[/C][C]-13.2125984251968[/C][/ROW]
[ROW][C]280[/C][C]66[/C][C]65.2125984251968[/C][C]0.787401574803155[/C][/ROW]
[ROW][C]281[/C][C]76[/C][C]65.2125984251968[/C][C]10.7874015748032[/C][/ROW]
[ROW][C]282[/C][C]43[/C][C]65.2125984251968[/C][C]-22.2125984251968[/C][/ROW]
[ROW][C]283[/C][C]39[/C][C]65.2125984251968[/C][C]-26.2125984251968[/C][/ROW]
[ROW][C]284[/C][C]14[/C][C]11.9375[/C][C]2.0625[/C][/ROW]
[ROW][C]285[/C][C]61[/C][C]65.2125984251968[/C][C]-4.21259842519684[/C][/ROW]
[ROW][C]286[/C][C]71[/C][C]65.2125984251968[/C][C]5.78740157480316[/C][/ROW]
[ROW][C]287[/C][C]44[/C][C]65.2125984251968[/C][C]-21.2125984251968[/C][/ROW]
[ROW][C]288[/C][C]60[/C][C]65.2125984251968[/C][C]-5.21259842519684[/C][/ROW]
[ROW][C]289[/C][C]64[/C][C]65.2125984251968[/C][C]-1.21259842519684[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=158821&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=158821&T=2

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Actuals, Predictions, and Residuals
#	Actuals	Forecasts	Residuals
1	115	129.75	-14.75
2	109	109.942857142857	-0.942857142857136
3	146	109.942857142857	36.0571428571429
4	116	129.75	-13.75
5	68	65.2125984251968	2.78740157480316
6	101	65.2125984251968	35.7874015748032
7	96	129.75	-33.75
8	67	49.9	17.1
9	44	65.2125984251968	-21.2125984251968
10	100	99.6666666666667	0.333333333333329
11	93	109.942857142857	-16.9428571428571
12	140	129.75	10.25
13	166	129.75	36.25
14	99	65.2125984251968	33.7874015748032
15	139	129.75	9.25
16	130	109.942857142857	20.0571428571429
17	181	129.75	51.25
18	116	129.75	-13.75
19	116	129.75	-13.75
20	88	129.75	-41.75
21	139	129.75	9.25
22	135	129.75	5.25
23	108	129.75	-21.75
24	89	99.6666666666667	-10.6666666666667
25	156	129.75	26.25
26	129	129.75	-0.75
27	118	109.942857142857	8.05714285714286
28	118	129.75	-11.75
29	125	129.75	-4.75
30	95	65.2125984251968	29.7874015748032
31	126	129.75	-3.75
32	135	129.75	5.25
33	154	99.6666666666667	54.3333333333333
34	165	129.75	35.25
35	113	65.2125984251968	47.7874015748032
36	127	129.75	-2.75
37	52	65.2125984251968	-13.2125984251968
38	121	109.942857142857	11.0571428571429
39	136	129.75	6.25
40	0	11.9375	-11.9375
41	108	109.942857142857	-1.94285714285714
42	46	65.2125984251968	-19.2125984251968
43	54	65.2125984251968	-11.2125984251968
44	124	129.75	-5.75
45	115	129.75	-14.75
46	128	109.942857142857	18.0571428571429
47	80	109.942857142857	-29.9428571428571
48	97	109.942857142857	-12.9428571428571
49	104	65.2125984251968	38.7874015748032
50	59	65.2125984251968	-6.21259842519684
51	125	129.75	-4.75
52	82	65.2125984251968	16.7874015748032
53	149	129.75	19.25
54	149	129.75	19.25
55	122	129.75	-7.75
56	118	129.75	-11.75
57	12	11.9375	0.0625
58	144	129.75	14.25
59	67	65.2125984251968	1.78740157480316
60	52	65.2125984251968	-13.2125984251968
61	108	129.75	-21.75
62	166	129.75	36.25
63	80	129.75	-49.75
64	60	65.2125984251968	-5.21259842519684
65	107	129.75	-22.75
66	127	129.75	-2.75
67	107	129.75	-22.75
68	146	129.75	16.25
69	84	129.75	-45.75
70	141	109.942857142857	31.0571428571429
71	123	109.942857142857	13.0571428571429
72	111	99.6666666666667	11.3333333333333
73	98	109.942857142857	-11.9428571428571
74	105	109.942857142857	-4.94285714285714
75	135	129.75	5.25
76	107	129.75	-22.75
77	85	129.75	-44.75
78	155	129.75	25.25
79	88	65.2125984251968	22.7874015748032
80	155	109.942857142857	45.0571428571429
81	104	109.942857142857	-5.94285714285714
82	132	129.75	2.25
83	127	129.75	-2.75
84	108	129.75	-21.75
85	129	109.942857142857	19.0571428571429
86	116	129.75	-13.75
87	122	109.942857142857	12.0571428571429
88	85	65.2125984251968	19.7874015748032
89	147	129.75	17.25
90	99	99.6666666666667	-0.666666666666671
91	87	129.75	-42.75
92	28	65.2125984251968	-37.2125984251968
93	90	65.2125984251968	24.7874015748032
94	109	109.942857142857	-0.942857142857136
95	78	65.2125984251968	12.7874015748032
96	111	109.942857142857	1.05714285714286
97	158	129.75	28.25
98	141	129.75	11.25
99	122	109.942857142857	12.0571428571429
100	124	129.75	-5.75
101	93	99.6666666666667	-6.66666666666667
102	124	129.75	-5.75
103	112	109.942857142857	2.05714285714286
104	108	109.942857142857	-1.94285714285714
105	99	129.75	-30.75
106	117	129.75	-12.75
107	199	129.75	69.25
108	78	65.2125984251968	12.7874015748032
109	91	129.75	-38.75
110	158	129.75	28.25
111	126	129.75	-3.75
112	122	99.6666666666667	22.3333333333333
113	71	49.9	21.1
114	75	109.942857142857	-34.9428571428571
115	115	129.75	-14.75
116	119	129.75	-10.75
117	124	129.75	-5.75
118	72	99.6666666666667	-27.6666666666667
119	91	65.2125984251968	25.7874015748032
120	45	65.2125984251968	-20.2125984251968
121	78	109.942857142857	-31.9428571428571
122	39	65.2125984251968	-26.2125984251968
123	68	65.2125984251968	2.78740157480316
124	119	129.75	-10.75
125	117	99.6666666666667	17.3333333333333
126	39	65.2125984251968	-26.2125984251968
127	50	65.2125984251968	-15.2125984251968
128	88	109.942857142857	-21.9428571428571
129	155	129.75	25.25
130	0	11.9375	-11.9375
131	36	49.9	-13.9
132	123	129.75	-6.75
133	32	65.2125984251968	-33.2125984251968
134	99	65.2125984251968	33.7874015748032
135	136	109.942857142857	26.0571428571429
136	117	129.75	-12.75
137	0	11.9375	-11.9375
138	88	109.942857142857	-21.9428571428571
139	39	49.9	-10.9
140	25	11.9375	13.0625
141	52	65.2125984251968	-13.2125984251968
142	75	109.942857142857	-34.9428571428571
143	71	65.2125984251968	5.78740157480316
144	124	129.75	-5.75
145	151	109.942857142857	41.0571428571429
146	71	65.2125984251968	5.78740157480316
147	145	65.2125984251968	79.7874015748032
148	87	65.2125984251968	21.7874015748032
149	27	49.9	-22.9
150	131	99.6666666666667	31.3333333333333
151	162	129.75	32.25
152	165	99.6666666666667	65.3333333333333
153	54	65.2125984251968	-11.2125984251968
154	159	129.75	29.25
155	147	129.75	17.25
156	170	129.75	40.25
157	119	109.942857142857	9.05714285714286
158	49	65.2125984251968	-16.2125984251968
159	104	65.2125984251968	38.7874015748032
160	120	109.942857142857	10.0571428571429
161	150	129.75	20.25
162	112	65.2125984251968	46.7874015748032
163	59	65.2125984251968	-6.21259842519684
164	136	129.75	6.25
165	107	65.2125984251968	41.7874015748032
166	130	129.75	0.25
167	115	109.942857142857	5.05714285714286
168	107	99.6666666666667	7.33333333333333
169	75	65.2125984251968	9.78740157480316
170	71	99.6666666666667	-28.6666666666667
171	120	129.75	-9.75
172	116	129.75	-13.75
173	79	99.6666666666667	-20.6666666666667
174	150	129.75	20.25
175	156	129.75	26.25
176	51	65.2125984251968	-14.2125984251968
177	118	129.75	-11.75
178	71	65.2125984251968	5.78740157480316
179	144	129.75	14.25
180	47	65.2125984251968	-18.2125984251968
181	28	65.2125984251968	-37.2125984251968
182	68	109.942857142857	-41.9428571428571
183	0	11.9375	-11.9375
184	110	99.6666666666667	10.3333333333333
185	147	129.75	17.25
186	0	11.9375	-11.9375
187	15	65.2125984251968	-50.2125984251968
188	4	11.9375	-7.9375
189	64	65.2125984251968	-1.21259842519684
190	111	65.2125984251968	45.7874015748032
191	85	99.6666666666667	-14.6666666666667
192	68	65.2125984251968	2.78740157480316
193	40	65.2125984251968	-25.2125984251968
194	80	65.2125984251968	14.7874015748032
195	88	99.6666666666667	-11.6666666666667
196	48	65.2125984251968	-17.2125984251968
197	76	65.2125984251968	10.7874015748032
198	51	65.2125984251968	-14.2125984251968
199	67	65.2125984251968	1.78740157480316
200	59	65.2125984251968	-6.21259842519684
201	61	65.2125984251968	-4.21259842519684
202	76	65.2125984251968	10.7874015748032
203	60	65.2125984251968	-5.21259842519684
204	68	65.2125984251968	2.78740157480316
205	71	65.2125984251968	5.78740157480316
206	76	65.2125984251968	10.7874015748032
207	62	65.2125984251968	-3.21259842519684
208	61	99.6666666666667	-38.6666666666667
209	67	65.2125984251968	1.78740157480316
210	88	65.2125984251968	22.7874015748032
211	30	65.2125984251968	-35.2125984251968
212	64	65.2125984251968	-1.21259842519684
213	68	65.2125984251968	2.78740157480316
214	64	65.2125984251968	-1.21259842519684
215	91	65.2125984251968	25.7874015748032
216	88	65.2125984251968	22.7874015748032
217	52	65.2125984251968	-13.2125984251968
218	49	65.2125984251968	-16.2125984251968
219	62	65.2125984251968	-3.21259842519684
220	61	65.2125984251968	-4.21259842519684
221	76	65.2125984251968	10.7874015748032
222	88	65.2125984251968	22.7874015748032
223	66	109.942857142857	-43.9428571428571
224	71	65.2125984251968	5.78740157480316
225	68	49.9	18.1
226	48	65.2125984251968	-17.2125984251968
227	25	65.2125984251968	-40.2125984251968
228	68	65.2125984251968	2.78740157480316
229	41	65.2125984251968	-24.2125984251968
230	90	65.2125984251968	24.7874015748032
231	66	49.9	16.1
232	54	65.2125984251968	-11.2125984251968
233	59	65.2125984251968	-6.21259842519684
234	60	65.2125984251968	-5.21259842519684
235	77	65.2125984251968	11.7874015748032
236	68	65.2125984251968	2.78740157480316
237	72	99.6666666666667	-27.6666666666667
238	67	65.2125984251968	1.78740157480316
239	64	65.2125984251968	-1.21259842519684
240	63	49.9	13.1
241	59	65.2125984251968	-6.21259842519684
242	84	99.6666666666667	-15.6666666666667
243	64	65.2125984251968	-1.21259842519684
244	56	65.2125984251968	-9.21259842519684
245	54	65.2125984251968	-11.2125984251968
246	67	65.2125984251968	1.78740157480316
247	58	65.2125984251968	-7.21259842519684
248	59	65.2125984251968	-6.21259842519684
249	40	65.2125984251968	-25.2125984251968
250	22	11.9375	10.0625
251	83	99.6666666666667	-16.6666666666667
252	81	65.2125984251968	15.7874015748032
253	2	11.9375	-9.9375
254	72	65.2125984251968	6.78740157480316
255	61	65.2125984251968	-4.21259842519684
256	15	11.9375	3.0625
257	32	11.9375	20.0625
258	62	65.2125984251968	-3.21259842519684
259	58	65.2125984251968	-7.21259842519684
260	36	11.9375	24.0625
261	59	49.9	9.1
262	68	65.2125984251968	2.78740157480316
263	21	11.9375	9.0625
264	55	65.2125984251968	-10.2125984251968
265	54	65.2125984251968	-11.2125984251968
266	55	65.2125984251968	-10.2125984251968
267	72	65.2125984251968	6.78740157480316
268	41	65.2125984251968	-24.2125984251968
269	61	65.2125984251968	-4.21259842519684
270	67	65.2125984251968	1.78740157480316
271	76	65.2125984251968	10.7874015748032
272	64	65.2125984251968	-1.21259842519684
273	3	49.9	-46.9
274	63	65.2125984251968	-2.21259842519684
275	40	65.2125984251968	-25.2125984251968
276	69	65.2125984251968	3.78740157480316
277	48	65.2125984251968	-17.2125984251968
278	8	11.9375	-3.9375
279	52	65.2125984251968	-13.2125984251968
280	66	65.2125984251968	0.787401574803155
281	76	65.2125984251968	10.7874015748032
282	43	65.2125984251968	-22.2125984251968
283	39	65.2125984251968	-26.2125984251968
284	14	11.9375	2.0625
285	61	65.2125984251968	-4.21259842519684
286	71	65.2125984251968	5.78740157480316
287	44	65.2125984251968	-21.2125984251968
288	60	65.2125984251968	-5.21259842519684
289	64	65.2125984251968	-1.21259842519684

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Figure 3

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 1 ; par2 = none ; par3 = 3 ; par4 = no ;

Parameters (R input):

par1 = 1 ; par2 = none ; par3 = 3 ; par4 = no ;

R code (references can be found in the software module):

library(party)
library(Hmisc)
par1 <- as.numeric(par1)
par3 <- as.numeric(par3)
x <- data.frame(t(y))
is.data.frame(x)
x <- x[!is.na(x[,par1]),]
k <- length(x[1,])
n <- length(x[,1])
colnames(x)[par1]
x[,par1]
if (par2 == 'kmeans') {
cl <- kmeans(x[,par1], par3)
print(cl)
clm <- matrix(cbind(cl$centers,1:par3),ncol=2)
clm <- clm[sort.list(clm[,1]),]
for (i in 1:par3) {
cl$cluster[cl$cluster==clm[i,2]] <- paste('C',i,sep='')
}
cl$cluster <- as.factor(cl$cluster)
print(cl$cluster)
x[,par1] <- cl$cluster
}
if (par2 == 'quantiles') {
x[,par1] <- cut2(x[,par1],g=par3)
}
if (par2 == 'hclust') {
hc <- hclust(dist(x[,par1])^2, 'cen')
print(hc)
memb <- cutree(hc, k = par3)
dum <- c(mean(x[memb==1,par1]))
for (i in 2:par3) {
dum <- c(dum, mean(x[memb==i,par1]))
}
hcm <- matrix(cbind(dum,1:par3),ncol=2)
hcm <- hcm[sort.list(hcm[,1]),]
for (i in 1:par3) {
memb[memb==hcm[i,2]] <- paste('C',i,sep='')
}
memb <- as.factor(memb)
print(memb)
x[,par1] <- memb
}
if (par2=='equal') {
ed <- cut(as.numeric(x[,par1]),par3,labels=paste('C',1:par3,sep=''))
x[,par1] <- as.factor(ed)
}
table(x[,par1])
colnames(x)
colnames(x)[par1]
x[,par1]
if (par2 == 'none') {
m <- ctree(as.formula(paste(colnames(x)[par1],' ~ .',sep='')),data = x)
}
load(file='createtable')
if (par2 != 'none') {
m <- ctree(as.formula(paste('as.factor(',colnames(x)[par1],') ~ .',sep='')),data = x)
if (par4=='yes') {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'10-Fold Cross Validation',3+2*par3,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'',1,TRUE)
a<-table.element(a,'Prediction (training)',par3+1,TRUE)
a<-table.element(a,'Prediction (testing)',par3+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Actual',1,TRUE)
for (jjj in 1:par3) a<-table.element(a,paste('C',jjj,sep=''),1,TRUE)
a<-table.element(a,'CV',1,TRUE)
for (jjj in 1:par3) a<-table.element(a,paste('C',jjj,sep=''),1,TRUE)
a<-table.element(a,'CV',1,TRUE)
a<-table.row.end(a)
for (i in 1:10) {
ind <- sample(2, nrow(x), replace=T, prob=c(0.9,0.1))
m.ct <- ctree(as.formula(paste('as.factor(',colnames(x)[par1],') ~ .',sep='')),data =x[ind==1,])
if (i==1) {
m.ct.i.pred <- predict(m.ct, newdata=x[ind==1,])
m.ct.i.actu <- x[ind==1,par1]
m.ct.x.pred <- predict(m.ct, newdata=x[ind==2,])
m.ct.x.actu <- x[ind==2,par1]
} else {
m.ct.i.pred <- c(m.ct.i.pred,predict(m.ct, newdata=x[ind==1,]))
m.ct.i.actu <- c(m.ct.i.actu,x[ind==1,par1])
m.ct.x.pred <- c(m.ct.x.pred,predict(m.ct, newdata=x[ind==2,]))
m.ct.x.actu <- c(m.ct.x.actu,x[ind==2,par1])
}
}
print(m.ct.i.tab <- table(m.ct.i.actu,m.ct.i.pred))
numer <- 0
for (i in 1:par3) {
print(m.ct.i.tab[i,i] / sum(m.ct.i.tab[i,]))
numer <- numer + m.ct.i.tab[i,i]
}
print(m.ct.i.cp <- numer / sum(m.ct.i.tab))
print(m.ct.x.tab <- table(m.ct.x.actu,m.ct.x.pred))
numer <- 0
for (i in 1:par3) {
print(m.ct.x.tab[i,i] / sum(m.ct.x.tab[i,]))
numer <- numer + m.ct.x.tab[i,i]
}
print(m.ct.x.cp <- numer / sum(m.ct.x.tab))
for (i in 1:par3) {
a<-table.row.start(a)
a<-table.element(a,paste('C',i,sep=''),1,TRUE)
for (jjj in 1:par3) a<-table.element(a,m.ct.i.tab[i,jjj])
a<-table.element(a,round(m.ct.i.tab[i,i]/sum(m.ct.i.tab[i,]),4))
for (jjj in 1:par3) a<-table.element(a,m.ct.x.tab[i,jjj])
a<-table.element(a,round(m.ct.x.tab[i,i]/sum(m.ct.x.tab[i,]),4))
a<-table.row.end(a)
}
a<-table.row.start(a)
a<-table.element(a,'Overall',1,TRUE)
for (jjj in 1:par3) a<-table.element(a,'-')
a<-table.element(a,round(m.ct.i.cp,4))
for (jjj in 1:par3) a<-table.element(a,'-')
a<-table.element(a,round(m.ct.x.cp,4))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
}
}
m
bitmap(file='test1.png')
plot(m)
dev.off()
bitmap(file='test1a.png')
plot(x[,par1] ~ as.factor(where(m)),main='Response by Terminal Node',xlab='Terminal Node',ylab='Response')
dev.off()
if (par2 == 'none') {
forec <- predict(m)
result <- as.data.frame(cbind(x[,par1],forec,x[,par1]-forec))
colnames(result) <- c('Actuals','Forecasts','Residuals')
print(result)
}
if (par2 != 'none') {
print(cbind(as.factor(x[,par1]),predict(m)))
myt <- table(as.factor(x[,par1]),predict(m))
print(myt)
}
bitmap(file='test2.png')
if(par2=='none') {
op <- par(mfrow=c(2,2))
plot(density(result$Actuals),main='Kernel Density Plot of Actuals')
plot(density(result$Residuals),main='Kernel Density Plot of Residuals')
plot(result$Forecasts,result$Actuals,main='Actuals versus Predictions',xlab='Predictions',ylab='Actuals')
plot(density(result$Forecasts),main='Kernel Density Plot of Predictions')
par(op)
}
if(par2!='none') {
plot(myt,main='Confusion Matrix',xlab='Actual',ylab='Predicted')
}
dev.off()
if (par2 == 'none') {
detcoef <- cor(result$Forecasts,result$Actuals)
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Goodness of Fit',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Correlation',1,TRUE)
a<-table.element(a,round(detcoef,4))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'R-squared',1,TRUE)
a<-table.element(a,round(detcoef*detcoef,4))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'RMSE',1,TRUE)
a<-table.element(a,round(sqrt(mean((result$Residuals)^2)),4))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Actuals, Predictions, and Residuals',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'#',header=TRUE)
a<-table.element(a,'Actuals',header=TRUE)
a<-table.element(a,'Forecasts',header=TRUE)
a<-table.element(a,'Residuals',header=TRUE)
a<-table.row.end(a)
for (i in 1:length(result$Actuals)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,result$Actuals[i])
a<-table.element(a,result$Forecasts[i])
a<-table.element(a,result$Residuals[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
}
if (par2 != 'none') {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Confusion Matrix (predicted in columns / actuals in rows)',par3+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'',1,TRUE)
for (i in 1:par3) {
a<-table.element(a,paste('C',i,sep=''),1,TRUE)
}
a<-table.row.end(a)
for (i in 1:par3) {
a<-table.row.start(a)
a<-table.element(a,paste('C',i,sep=''),1,TRUE)
for (j in 1:par3) {
a<-table.element(a,myt[i,j])
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
}

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code