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Author

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R Software Module

rwasp_regression_trees1.wasp

Title produced by software

Recursive Partitioning (Regression Trees)

Date of computation

Sun, 16 Dec 2012 13:24:55 -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/2012/Dec/16/t1355682313sbn0vyrwsohbfmv.htm/, Retrieved Thu, 25 Apr 2024 17:27:13 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=200541, Retrieved Thu, 25 Apr 2024 17:27:13 +0000

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Original text written by user:

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No (this computation is public)

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Estimated Impact

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

-       [Recursive Partitioning (Regression Trees)] [Regressieboom Lon...] [2012-12-16 18:24:55] [acfd67cb214b61d0a5e0fb4c8c6ef02a] [Current]

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Dataseries X:

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46	310232,86	41,761	0,939	0,923	0,869
38	1330141,29	6,2	0,623	0,843	0,618
24	139390,2	13,611	0,784	0,77	0,713
29	62348,45	32,147	0,815	0,949	0,832
11	81644,45	32,255	0,928	0,953	0,838
11	64768,39	29,578	0,87	0,971	0,819
13	48636,07	25,493	0,934	0,956	0,808
7	126804,43	29,692	0,883	1.000	0,827
7	21515,75	34,259	0,981	0,976	0,837
8	60748,96	26,578	0,856	0,976	0,799
8	9992,34	16,896	0,866	0,858	0,732
6	16783,09	36,358	0,931	0,958	0,845
6	45415,6	5,737	0,858	0,765	0,591
7	15460,48	10,452	0,834	0,742	0,668
6	4252,28	24,706	1.000	0,957	0,783
3	46505,96	27,066	0,874	0,969	0,799
3	201103,33	9,414	0,663	0,844	0,662
4	76923,3	10,496	0,64	0,836	0,662
4	2847,23	6,931	0,768	0,838	0,598
4	10201,71	22,098	0,924	0,91	0,769
1	33759,74	34,567	0,927	0,962	0,84
2	9612,63	11,841	0,776	0,794	0,702
2	40046,57	1,428	0,582	0,586	0,387
2	21959,28	10,794	0,831	0,851	0,674
2	5515,57	32,252	0,924	0,928	0,836
2	8303,51	8,752	0,671	0,8	0,639
3	88013,49	848	0,237	0,619	0,326
2	38463,69	16,705	0,822	0,885	0,739
3	49109,11	9,333	0,705	0,517	0,652
3	4486,88	16,338	0,778	0,893	0,724
1	9074,06	32,314	0,904	0,969	0,842
1	44205,29	8,136	0,667	0,847	0,633
2	77804,12	11,209	0,583	0,851	0,689
1	4600,82	4,335	0,839	0,848	0,554
2	3545,32	15,011	0,883	0,824	0,729
1	112468,85	12,429	0,726	0,898	0,7
2	7623,44	36,954	0,872	0,983	0,858
2	4676,31	47,676	0,985	0,964	0,883
1	4622,92	36,278	0,963	0,955	0,814
1	41343,2	13,202	0,806	0,882	0,713
1	7344,85	9,967	0,79	0,86	0,663
1	2003,14	24,806	0,933	0,936	0,79
0	1173108,02	2,993	0,45	0,717	0,508
1	1228,69	23,221	0,712	0,791	0,782
1	10525,04	7,512	0,645	0,86	0,614
1	27865,74	2,611	0,711	0,762	0,486
1	9823,82	7,658	0,616	0,842	0,629
0	3086,92	3,198	0,722	0,765	0,505
1	2217,97	12,847	0,873	0,841	0,711
1	34586,18	7,421	0,652	0,838	0,621
1	107,82	7,593	0,779	0,883	0,608
0	5470,31	19,202	0,875	0,875	0,759
0	66336,26	7,26	0,597	0,854	0,622
1	33398,68	1,105	0,475	0,538	0,347
1	27223,23	11,19	0,692	0,858	0,669
0	2966,8	4,794	0,76	0,856	0,566
0	10423,49	32,395	0,882	0,947	0,832
0	80471,87	5,151	0,56	0,84	0,568
0	5255,07	30,784	0,877	0,946	0,828
0	7148,78	11,456	0,802	0,842	0,678
0	1291,17	16,132	0,916	0,865	0,734
0	242968,34	3,813	0,584	0,779	0,518
0	28274,73	12,724	0,73	0,855	0,704
0	2029,31	12,154	0,693	0,523	0,698
0	1102,68	25,759	0,798	0,94	0,79
0	1545,26	13,094	0,66	0,674	0,689
0	10749,94	26,482	0,861	0,945	0,783
0	13550,44	4,286	0,438	0,807	0,534
0	666,73	10,022	0,802	0,861	0,665
0	10735,76	21,37	0,739	0,938	0,763
0	840,93	82,978	0,623	0,921	1.000
0	4317,48	2,592	0,716	0,778	0,49
0	4701,07	45,978	0,751	0,964	0,897
0	29121,29	1,20	0,367	0,452	0,38
0	7089,7	39,255	0,837	0,99	0,874
0	31627,43	4,081	0,447	0,823	0,535
0	25731,78	21,321	0,689	0,85	0,781
0	7487,49	1,791	0,704	0,75	0,425
0	2986,95	7,449	0,721	0,898	0,624
0	13068,16	5,278	0,422	0,49	0,557
0	86,75	17,052	0,744	0,83	0,723
0	8214,16	34,673	0,858	0,96	0,842
0	156118,46	1,286	0,415	0,772	0,391
0	314,52	6,019	0,663	0,884	0,582
0	9056,01	1,369	0,365	0,569	0,374
0	699,85	4,643	0,336	0,744	0,568
0	9947,42	4,013	0,749	0,735	0,53
0	4621,6	7,266	0,723	0,878	0,621
0	16241,81	1,078	0,187	0,559	0,349
0	9863,12	356	0,353	0,48	0,186
0	14453,68	1,739	0,502	0,68	0,418
0	19294,15	2,002	0,52	0,499	0,431
0	508,66	3,309	0,425	0,854	0,505
0	4844,93	688	0,321	0,448	0,28
0	10543,46	1,181	0,219	0,466	0,344
0	16746,49	13,057	0,797	0,932	0,701
0	773,41	1,074	0,368	0,648	0,341
0	4125,92	3,848	0,523	0,59	0,49
0	4516,22	10,085	0,659	0,936	0,667
0	21058,8	1,545	0,304	0,558	0,377
0	740,53	2,106	0,294	0,598	0,451
0	72,81	8,066	0,67	0,907	0,626
0	69851,29	290	0,356	0,448	0,147
0	14790,61	7,508	0,686	0,877	0,62
0	6052,06	6,02	0,637	0,823	0,585
0	650,7	28,857	0,427	0,49	0,741
0	5792,98	527	0,271	0,656	0,24
0	875,98	4,11	0,786	0,777	0,533
0	1755,46	1,285	0,334	0,607	0,365
0	24339,84	1,41	0,574	0,698	0,396
0	10324,02	951	0,246	0,538	0,309
0	1565,13	973	0,302	0,444	0,329
0	748,49	2,942	0,65	0,787	0,496
0	9648,92	1,045	0,406	0,664	0,346
0	7989,41	3,488	0,574	0,838	0,507
0	308,91	33,98	0,912	0,975	0,814
0	29671,6	3,222	0,491	0,774	0,495
0	7353,98	25,474	0,907	0,972	0,796
0	6407,09	5,082	0,71	0,842	0,569
0	99,48	2,209	0,647	0,759	0,494
0	5508,63	2,073	0,716	0,753	0,432
0	6368,16	2,048	0,432	0,749	0,445
0	4125,25	11,868	0,695	0,83	0,698
0	1919,55	1,333	0,507	0,445	0,403
0	3685,08	360	0,439	0,58	0,14
0	6461,45	14,985	0,731	0,864	0,693
0	497,54	68,853	0,771	0,946	0,892
0	21281,84	912	0,497	0,737	0,302
0	15447,5	721	0,41	0,54	0,289
0	395,65	4,972	0,568	0,897	0,568
0	13796,35	1,077	0,27	0,496	0,346
0	406,77	21,987	0,797	0,941	0,769
0	3205,06	1,751	0,366	0,609	0,419
0	1294,1	11,658	0,659	0,842	0,696
0	107,15	2,804	0,689	0,773	0,484
0	22417,45	804	0,222	0,477	0,314
0	2128,47	5,821	0,617	0,67	0,591
0	28951,85	1,049	0,356	0,77	0,351
0	5604,45	2,398	0,525	0,852	0,457
0	15878,27	626	0,177	0,547	0,266
0	152217,34	2,001	0,442	0,503	0,434
0	184404,79	2,369	0,386	0,717	0,464
0	3410,68	11,857	0,743	0,885	0,69
0	6064,52	2,072	0,335	0,675	0,447
0	6375,83	4,107	0,643	0,828	0,552
0	28947,97	7,836	0,704	0,852	0,634
0	99900,18	3,216	0,684	0,769	0,508
0	11055,98	1,032	0,407	0,559	0,348
0	175,81	1,653	0,452	0,705	0,413
0	160,92	8,722	0,693	0,862	0,632
0	192	4	0,75	0,827	0,526
0	12323,25	1,65	0,385	0,62	0,406
0	88,34	17,786	0,747	0,845	0,733
0	5245,69	734	0,304	0,438	0,286
0	559,2	2,312	0,427	0,755	0,413
0	21083,83	4,333	0,68	0,867	0,559
0	49,9	13,191	0,693	0,838	0,684
0	104,22	8,312	0,712	0,825	0,628
0	43939,6	2,007	0,247	0,654	0,421
0	1354,05	4,539	0,578	0,453	0,545
0	22198,11	4,295	0,534	0,881	0,537
0	41892,89	1,237	0,454	0,603	0,37
0	1154,62	731	0,371	0,67	0,487
0	6587,24	772	0,473	0,585	0,297
0	105,63	4,055	0,79	0,825	0,535
0	4940,92	6,576	0,739	0,71	0,615
0	4975,59	52,435	0,741	0,892	0,916
0	3301,08	11,977	0,763	0,899	0,7
0	221,55	4,03	0,554	0,805	0,527
0	89571,13	2,682	0,503	0,87	0,478
0	23495,36	2,243	0,31	0,718	0,444
0	13460,31	1,299	0,48	0,458	0,362

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	'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=200541&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=200541&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=200541&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	'Gertrude Mary Cox' @ cox.wessa.net

Goodness of Fit
Correlation	0.4893
R-squared	0.2395
RMSE	4.8983

\begin{tabular}{lllllllll}
\hline
Goodness of Fit \tabularnewline
Correlation & 0.4893 \tabularnewline
R-squared & 0.2395 \tabularnewline
RMSE & 4.8983 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=200541&T=1

[TABLE]
[ROW][C]Goodness of Fit[/C][/ROW]
[ROW][C]Correlation[/C][C]0.4893[/C][/ROW]
[ROW][C]R-squared[/C][C]0.2395[/C][/ROW]
[ROW][C]RMSE[/C][C]4.8983[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=200541&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=200541&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	0.4893
R-squared	0.2395
RMSE	4.8983

Actuals, Predictions, and Residuals
#	Actuals	Forecasts	Residuals
1	46	7.85185185185185	38.1481481481481
2	38	7.85185185185185	30.1481481481481
3	24	7.85185185185185	16.1481481481481
4	29	7.85185185185185	21.1481481481481
5	11	7.85185185185185	3.14814814814815
6	11	7.85185185185185	3.14814814814815
7	13	7.85185185185185	5.14814814814815
8	7	7.85185185185185	-0.851851851851852
9	7	2.07407407407407	4.92592592592593
10	8	7.85185185185185	0.148148148148148
11	8	2.07407407407407	5.92592592592593
12	6	2.07407407407407	3.92592592592593
13	6	7.85185185185185	-1.85185185185185
14	7	2.07407407407407	4.92592592592593
15	6	2.07407407407407	3.92592592592593
16	3	7.85185185185185	-4.85185185185185
17	3	7.85185185185185	-4.85185185185185
18	4	7.85185185185185	-3.85185185185185
19	4	0.857142857142857	3.14285714285714
20	4	2.07407407407407	1.92592592592593
21	1	2.07407407407407	-1.07407407407407
22	2	0.857142857142857	1.14285714285714
23	2	0.714285714285714	1.28571428571429
24	2	2.07407407407407	-0.074074074074074
25	2	2.07407407407407	-0.074074074074074
26	2	0.0721649484536082	1.92783505154639
27	3	7.85185185185185	-4.85185185185185
28	2	2.07407407407407	-0.074074074074074
29	3	7.85185185185185	-4.85185185185185
30	3	0.857142857142857	2.14285714285714
31	1	2.07407407407407	-1.07407407407407
32	1	0.714285714285714	0.285714285714286
33	2	7.85185185185185	-5.85185185185185
34	1	2.07407407407407	-1.07407407407407
35	2	2.07407407407407	-0.074074074074074
36	1	7.85185185185185	-6.85185185185185
37	2	2.07407407407407	-0.074074074074074
38	2	2.07407407407407	-0.074074074074074
39	1	2.07407407407407	-1.07407407407407
40	1	0.857142857142857	0.142857142857143
41	1	0.857142857142857	0.142857142857143
42	1	2.07407407407407	-1.07407407407407
43	0	7.85185185185185	-7.85185185185185
44	1	0.0721649484536082	0.927835051546392
45	1	0.0721649484536082	0.927835051546392
46	1	0.0721649484536082	0.927835051546392
47	1	0.0721649484536082	0.927835051546392
48	0	0.0721649484536082	-0.0721649484536082
49	1	2.07407407407407	-1.07407407407407
50	1	0.714285714285714	0.285714285714286
51	1	0.857142857142857	0.142857142857143
52	0	2.07407407407407	-2.07407407407407
53	0	7.85185185185185	-7.85185185185185
54	1	0.714285714285714	0.285714285714286
55	1	0.0721649484536082	0.927835051546392
56	0	0.0721649484536082	-0.0721649484536082
57	0	2.07407407407407	-2.07407407407407
58	0	7.85185185185185	-7.85185185185185
59	0	2.07407407407407	-2.07407407407407
60	0	0.857142857142857	-0.857142857142857
61	0	2.07407407407407	-2.07407407407407
62	0	7.85185185185185	-7.85185185185185
63	0	0.0721649484536082	-0.0721649484536082
64	0	0.0721649484536082	-0.0721649484536082
65	0	0.857142857142857	-0.857142857142857
66	0	0.0721649484536082	-0.0721649484536082
67	0	2.07407407407407	-2.07407407407407
68	0	0.0721649484536082	-0.0721649484536082
69	0	0.857142857142857	-0.857142857142857
70	0	0.0721649484536082	-0.0721649484536082
71	0	0.0721649484536082	-0.0721649484536082
72	0	0.0721649484536082	-0.0721649484536082
73	0	0.0721649484536082	-0.0721649484536082
74	0	0.0721649484536082	-0.0721649484536082
75	0	2.07407407407407	-2.07407407407407
76	0	0.714285714285714	-0.714285714285714
77	0	0.0721649484536082	-0.0721649484536082
78	0	0.0721649484536082	-0.0721649484536082
79	0	0.0721649484536082	-0.0721649484536082
80	0	0.0721649484536082	-0.0721649484536082
81	0	0.0721649484536082	-0.0721649484536082
82	0	2.07407407407407	-2.07407407407407
83	0	7.85185185185185	-7.85185185185185
84	0	0.0721649484536082	-0.0721649484536082
85	0	0.0721649484536082	-0.0721649484536082
86	0	0.0721649484536082	-0.0721649484536082
87	0	0.0721649484536082	-0.0721649484536082
88	0	0.0721649484536082	-0.0721649484536082
89	0	0.0721649484536082	-0.0721649484536082
90	0	0.0721649484536082	-0.0721649484536082
91	0	0.0721649484536082	-0.0721649484536082
92	0	0.0721649484536082	-0.0721649484536082
93	0	0.0721649484536082	-0.0721649484536082
94	0	0.0721649484536082	-0.0721649484536082
95	0	0.0721649484536082	-0.0721649484536082
96	0	0.857142857142857	-0.857142857142857
97	0	0.0721649484536082	-0.0721649484536082
98	0	0.0721649484536082	-0.0721649484536082
99	0	0.0721649484536082	-0.0721649484536082
100	0	0.0721649484536082	-0.0721649484536082
101	0	0.0721649484536082	-0.0721649484536082
102	0	0.0721649484536082	-0.0721649484536082
103	0	7.85185185185185	-7.85185185185185
104	0	0.0721649484536082	-0.0721649484536082
105	0	0.0721649484536082	-0.0721649484536082
106	0	0.0721649484536082	-0.0721649484536082
107	0	0.0721649484536082	-0.0721649484536082
108	0	0.857142857142857	-0.857142857142857
109	0	0.0721649484536082	-0.0721649484536082
110	0	0.0721649484536082	-0.0721649484536082
111	0	0.0721649484536082	-0.0721649484536082
112	0	0.0721649484536082	-0.0721649484536082
113	0	0.0721649484536082	-0.0721649484536082
114	0	0.0721649484536082	-0.0721649484536082
115	0	0.0721649484536082	-0.0721649484536082
116	0	2.07407407407407	-2.07407407407407
117	0	0.0721649484536082	-0.0721649484536082
118	0	2.07407407407407	-2.07407407407407
119	0	0.0721649484536082	-0.0721649484536082
120	0	0.0721649484536082	-0.0721649484536082
121	0	0.0721649484536082	-0.0721649484536082
122	0	0.0721649484536082	-0.0721649484536082
123	0	0.0721649484536082	-0.0721649484536082
124	0	0.0721649484536082	-0.0721649484536082
125	0	0.0721649484536082	-0.0721649484536082
126	0	0.0721649484536082	-0.0721649484536082
127	0	0.857142857142857	-0.857142857142857
128	0	0.0721649484536082	-0.0721649484536082
129	0	0.0721649484536082	-0.0721649484536082
130	0	0.0721649484536082	-0.0721649484536082
131	0	0.0721649484536082	-0.0721649484536082
132	0	0.857142857142857	-0.857142857142857
133	0	0.0721649484536082	-0.0721649484536082
134	0	0.0721649484536082	-0.0721649484536082
135	0	0.0721649484536082	-0.0721649484536082
136	0	0.0721649484536082	-0.0721649484536082
137	0	0.0721649484536082	-0.0721649484536082
138	0	0.0721649484536082	-0.0721649484536082
139	0	0.0721649484536082	-0.0721649484536082
140	0	0.0721649484536082	-0.0721649484536082
141	0	7.85185185185185	-7.85185185185185
142	0	7.85185185185185	-7.85185185185185
143	0	0.0721649484536082	-0.0721649484536082
144	0	0.0721649484536082	-0.0721649484536082
145	0	0.0721649484536082	-0.0721649484536082
146	0	0.0721649484536082	-0.0721649484536082
147	0	7.85185185185185	-7.85185185185185
148	0	0.0721649484536082	-0.0721649484536082
149	0	0.0721649484536082	-0.0721649484536082
150	0	0.0721649484536082	-0.0721649484536082
151	0	0.0721649484536082	-0.0721649484536082
152	0	0.0721649484536082	-0.0721649484536082
153	0	0.0721649484536082	-0.0721649484536082
154	0	0.0721649484536082	-0.0721649484536082
155	0	0.0721649484536082	-0.0721649484536082
156	0	0.0721649484536082	-0.0721649484536082
157	0	0.0721649484536082	-0.0721649484536082
158	0	0.0721649484536082	-0.0721649484536082
159	0	0.714285714285714	-0.714285714285714
160	0	0.0721649484536082	-0.0721649484536082
161	0	0.0721649484536082	-0.0721649484536082
162	0	0.714285714285714	-0.714285714285714
163	0	0.0721649484536082	-0.0721649484536082
164	0	0.0721649484536082	-0.0721649484536082
165	0	0.857142857142857	-0.857142857142857
166	0	0.0721649484536082	-0.0721649484536082
167	0	0.0721649484536082	-0.0721649484536082
168	0	0.0721649484536082	-0.0721649484536082
169	0	0.0721649484536082	-0.0721649484536082
170	0	7.85185185185185	-7.85185185185185
171	0	0.0721649484536082	-0.0721649484536082
172	0	0.0721649484536082	-0.0721649484536082

\begin{tabular}{lllllllll}
\hline
Actuals, Predictions, and Residuals \tabularnewline
# & Actuals & Forecasts & Residuals \tabularnewline
1 & 46 & 7.85185185185185 & 38.1481481481481 \tabularnewline
2 & 38 & 7.85185185185185 & 30.1481481481481 \tabularnewline
3 & 24 & 7.85185185185185 & 16.1481481481481 \tabularnewline
4 & 29 & 7.85185185185185 & 21.1481481481481 \tabularnewline
5 & 11 & 7.85185185185185 & 3.14814814814815 \tabularnewline
6 & 11 & 7.85185185185185 & 3.14814814814815 \tabularnewline
7 & 13 & 7.85185185185185 & 5.14814814814815 \tabularnewline
8 & 7 & 7.85185185185185 & -0.851851851851852 \tabularnewline
9 & 7 & 2.07407407407407 & 4.92592592592593 \tabularnewline
10 & 8 & 7.85185185185185 & 0.148148148148148 \tabularnewline
11 & 8 & 2.07407407407407 & 5.92592592592593 \tabularnewline
12 & 6 & 2.07407407407407 & 3.92592592592593 \tabularnewline
13 & 6 & 7.85185185185185 & -1.85185185185185 \tabularnewline
14 & 7 & 2.07407407407407 & 4.92592592592593 \tabularnewline
15 & 6 & 2.07407407407407 & 3.92592592592593 \tabularnewline
16 & 3 & 7.85185185185185 & -4.85185185185185 \tabularnewline
17 & 3 & 7.85185185185185 & -4.85185185185185 \tabularnewline
18 & 4 & 7.85185185185185 & -3.85185185185185 \tabularnewline
19 & 4 & 0.857142857142857 & 3.14285714285714 \tabularnewline
20 & 4 & 2.07407407407407 & 1.92592592592593 \tabularnewline
21 & 1 & 2.07407407407407 & -1.07407407407407 \tabularnewline
22 & 2 & 0.857142857142857 & 1.14285714285714 \tabularnewline
23 & 2 & 0.714285714285714 & 1.28571428571429 \tabularnewline
24 & 2 & 2.07407407407407 & -0.074074074074074 \tabularnewline
25 & 2 & 2.07407407407407 & -0.074074074074074 \tabularnewline
26 & 2 & 0.0721649484536082 & 1.92783505154639 \tabularnewline
27 & 3 & 7.85185185185185 & -4.85185185185185 \tabularnewline
28 & 2 & 2.07407407407407 & -0.074074074074074 \tabularnewline
29 & 3 & 7.85185185185185 & -4.85185185185185 \tabularnewline
30 & 3 & 0.857142857142857 & 2.14285714285714 \tabularnewline
31 & 1 & 2.07407407407407 & -1.07407407407407 \tabularnewline
32 & 1 & 0.714285714285714 & 0.285714285714286 \tabularnewline
33 & 2 & 7.85185185185185 & -5.85185185185185 \tabularnewline
34 & 1 & 2.07407407407407 & -1.07407407407407 \tabularnewline
35 & 2 & 2.07407407407407 & -0.074074074074074 \tabularnewline
36 & 1 & 7.85185185185185 & -6.85185185185185 \tabularnewline
37 & 2 & 2.07407407407407 & -0.074074074074074 \tabularnewline
38 & 2 & 2.07407407407407 & -0.074074074074074 \tabularnewline
39 & 1 & 2.07407407407407 & -1.07407407407407 \tabularnewline
40 & 1 & 0.857142857142857 & 0.142857142857143 \tabularnewline
41 & 1 & 0.857142857142857 & 0.142857142857143 \tabularnewline
42 & 1 & 2.07407407407407 & -1.07407407407407 \tabularnewline
43 & 0 & 7.85185185185185 & -7.85185185185185 \tabularnewline
44 & 1 & 0.0721649484536082 & 0.927835051546392 \tabularnewline
45 & 1 & 0.0721649484536082 & 0.927835051546392 \tabularnewline
46 & 1 & 0.0721649484536082 & 0.927835051546392 \tabularnewline
47 & 1 & 0.0721649484536082 & 0.927835051546392 \tabularnewline
48 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
49 & 1 & 2.07407407407407 & -1.07407407407407 \tabularnewline
50 & 1 & 0.714285714285714 & 0.285714285714286 \tabularnewline
51 & 1 & 0.857142857142857 & 0.142857142857143 \tabularnewline
52 & 0 & 2.07407407407407 & -2.07407407407407 \tabularnewline
53 & 0 & 7.85185185185185 & -7.85185185185185 \tabularnewline
54 & 1 & 0.714285714285714 & 0.285714285714286 \tabularnewline
55 & 1 & 0.0721649484536082 & 0.927835051546392 \tabularnewline
56 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
57 & 0 & 2.07407407407407 & -2.07407407407407 \tabularnewline
58 & 0 & 7.85185185185185 & -7.85185185185185 \tabularnewline
59 & 0 & 2.07407407407407 & -2.07407407407407 \tabularnewline
60 & 0 & 0.857142857142857 & -0.857142857142857 \tabularnewline
61 & 0 & 2.07407407407407 & -2.07407407407407 \tabularnewline
62 & 0 & 7.85185185185185 & -7.85185185185185 \tabularnewline
63 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
64 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
65 & 0 & 0.857142857142857 & -0.857142857142857 \tabularnewline
66 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
67 & 0 & 2.07407407407407 & -2.07407407407407 \tabularnewline
68 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
69 & 0 & 0.857142857142857 & -0.857142857142857 \tabularnewline
70 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
71 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
72 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
73 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
74 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
75 & 0 & 2.07407407407407 & -2.07407407407407 \tabularnewline
76 & 0 & 0.714285714285714 & -0.714285714285714 \tabularnewline
77 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
78 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
79 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
80 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
81 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
82 & 0 & 2.07407407407407 & -2.07407407407407 \tabularnewline
83 & 0 & 7.85185185185185 & -7.85185185185185 \tabularnewline
84 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
85 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
86 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
87 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
88 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
89 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
90 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
91 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
92 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
93 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
94 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
95 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
96 & 0 & 0.857142857142857 & -0.857142857142857 \tabularnewline
97 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
98 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
99 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
100 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
101 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
102 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
103 & 0 & 7.85185185185185 & -7.85185185185185 \tabularnewline
104 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
105 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
106 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
107 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
108 & 0 & 0.857142857142857 & -0.857142857142857 \tabularnewline
109 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
110 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
111 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
112 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
113 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
114 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
115 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
116 & 0 & 2.07407407407407 & -2.07407407407407 \tabularnewline
117 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
118 & 0 & 2.07407407407407 & -2.07407407407407 \tabularnewline
119 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
120 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
121 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
122 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
123 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
124 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
125 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
126 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
127 & 0 & 0.857142857142857 & -0.857142857142857 \tabularnewline
128 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
129 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
130 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
131 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
132 & 0 & 0.857142857142857 & -0.857142857142857 \tabularnewline
133 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
134 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
135 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
136 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
137 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
138 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
139 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
140 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
141 & 0 & 7.85185185185185 & -7.85185185185185 \tabularnewline
142 & 0 & 7.85185185185185 & -7.85185185185185 \tabularnewline
143 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
144 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
145 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
146 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
147 & 0 & 7.85185185185185 & -7.85185185185185 \tabularnewline
148 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
149 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
150 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
151 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
152 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
153 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
154 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
155 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
156 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
157 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
158 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
159 & 0 & 0.714285714285714 & -0.714285714285714 \tabularnewline
160 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
161 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
162 & 0 & 0.714285714285714 & -0.714285714285714 \tabularnewline
163 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
164 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
165 & 0 & 0.857142857142857 & -0.857142857142857 \tabularnewline
166 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
167 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
168 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
169 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
170 & 0 & 7.85185185185185 & -7.85185185185185 \tabularnewline
171 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
172 & 0 & 0.0721649484536082 & -0.0721649484536082 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=200541&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]46[/C][C]7.85185185185185[/C][C]38.1481481481481[/C][/ROW]
[ROW][C]2[/C][C]38[/C][C]7.85185185185185[/C][C]30.1481481481481[/C][/ROW]
[ROW][C]3[/C][C]24[/C][C]7.85185185185185[/C][C]16.1481481481481[/C][/ROW]
[ROW][C]4[/C][C]29[/C][C]7.85185185185185[/C][C]21.1481481481481[/C][/ROW]
[ROW][C]5[/C][C]11[/C][C]7.85185185185185[/C][C]3.14814814814815[/C][/ROW]
[ROW][C]6[/C][C]11[/C][C]7.85185185185185[/C][C]3.14814814814815[/C][/ROW]
[ROW][C]7[/C][C]13[/C][C]7.85185185185185[/C][C]5.14814814814815[/C][/ROW]
[ROW][C]8[/C][C]7[/C][C]7.85185185185185[/C][C]-0.851851851851852[/C][/ROW]
[ROW][C]9[/C][C]7[/C][C]2.07407407407407[/C][C]4.92592592592593[/C][/ROW]
[ROW][C]10[/C][C]8[/C][C]7.85185185185185[/C][C]0.148148148148148[/C][/ROW]
[ROW][C]11[/C][C]8[/C][C]2.07407407407407[/C][C]5.92592592592593[/C][/ROW]
[ROW][C]12[/C][C]6[/C][C]2.07407407407407[/C][C]3.92592592592593[/C][/ROW]
[ROW][C]13[/C][C]6[/C][C]7.85185185185185[/C][C]-1.85185185185185[/C][/ROW]
[ROW][C]14[/C][C]7[/C][C]2.07407407407407[/C][C]4.92592592592593[/C][/ROW]
[ROW][C]15[/C][C]6[/C][C]2.07407407407407[/C][C]3.92592592592593[/C][/ROW]
[ROW][C]16[/C][C]3[/C][C]7.85185185185185[/C][C]-4.85185185185185[/C][/ROW]
[ROW][C]17[/C][C]3[/C][C]7.85185185185185[/C][C]-4.85185185185185[/C][/ROW]
[ROW][C]18[/C][C]4[/C][C]7.85185185185185[/C][C]-3.85185185185185[/C][/ROW]
[ROW][C]19[/C][C]4[/C][C]0.857142857142857[/C][C]3.14285714285714[/C][/ROW]
[ROW][C]20[/C][C]4[/C][C]2.07407407407407[/C][C]1.92592592592593[/C][/ROW]
[ROW][C]21[/C][C]1[/C][C]2.07407407407407[/C][C]-1.07407407407407[/C][/ROW]
[ROW][C]22[/C][C]2[/C][C]0.857142857142857[/C][C]1.14285714285714[/C][/ROW]
[ROW][C]23[/C][C]2[/C][C]0.714285714285714[/C][C]1.28571428571429[/C][/ROW]
[ROW][C]24[/C][C]2[/C][C]2.07407407407407[/C][C]-0.074074074074074[/C][/ROW]
[ROW][C]25[/C][C]2[/C][C]2.07407407407407[/C][C]-0.074074074074074[/C][/ROW]
[ROW][C]26[/C][C]2[/C][C]0.0721649484536082[/C][C]1.92783505154639[/C][/ROW]
[ROW][C]27[/C][C]3[/C][C]7.85185185185185[/C][C]-4.85185185185185[/C][/ROW]
[ROW][C]28[/C][C]2[/C][C]2.07407407407407[/C][C]-0.074074074074074[/C][/ROW]
[ROW][C]29[/C][C]3[/C][C]7.85185185185185[/C][C]-4.85185185185185[/C][/ROW]
[ROW][C]30[/C][C]3[/C][C]0.857142857142857[/C][C]2.14285714285714[/C][/ROW]
[ROW][C]31[/C][C]1[/C][C]2.07407407407407[/C][C]-1.07407407407407[/C][/ROW]
[ROW][C]32[/C][C]1[/C][C]0.714285714285714[/C][C]0.285714285714286[/C][/ROW]
[ROW][C]33[/C][C]2[/C][C]7.85185185185185[/C][C]-5.85185185185185[/C][/ROW]
[ROW][C]34[/C][C]1[/C][C]2.07407407407407[/C][C]-1.07407407407407[/C][/ROW]
[ROW][C]35[/C][C]2[/C][C]2.07407407407407[/C][C]-0.074074074074074[/C][/ROW]
[ROW][C]36[/C][C]1[/C][C]7.85185185185185[/C][C]-6.85185185185185[/C][/ROW]
[ROW][C]37[/C][C]2[/C][C]2.07407407407407[/C][C]-0.074074074074074[/C][/ROW]
[ROW][C]38[/C][C]2[/C][C]2.07407407407407[/C][C]-0.074074074074074[/C][/ROW]
[ROW][C]39[/C][C]1[/C][C]2.07407407407407[/C][C]-1.07407407407407[/C][/ROW]
[ROW][C]40[/C][C]1[/C][C]0.857142857142857[/C][C]0.142857142857143[/C][/ROW]
[ROW][C]41[/C][C]1[/C][C]0.857142857142857[/C][C]0.142857142857143[/C][/ROW]
[ROW][C]42[/C][C]1[/C][C]2.07407407407407[/C][C]-1.07407407407407[/C][/ROW]
[ROW][C]43[/C][C]0[/C][C]7.85185185185185[/C][C]-7.85185185185185[/C][/ROW]
[ROW][C]44[/C][C]1[/C][C]0.0721649484536082[/C][C]0.927835051546392[/C][/ROW]
[ROW][C]45[/C][C]1[/C][C]0.0721649484536082[/C][C]0.927835051546392[/C][/ROW]
[ROW][C]46[/C][C]1[/C][C]0.0721649484536082[/C][C]0.927835051546392[/C][/ROW]
[ROW][C]47[/C][C]1[/C][C]0.0721649484536082[/C][C]0.927835051546392[/C][/ROW]
[ROW][C]48[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]49[/C][C]1[/C][C]2.07407407407407[/C][C]-1.07407407407407[/C][/ROW]
[ROW][C]50[/C][C]1[/C][C]0.714285714285714[/C][C]0.285714285714286[/C][/ROW]
[ROW][C]51[/C][C]1[/C][C]0.857142857142857[/C][C]0.142857142857143[/C][/ROW]
[ROW][C]52[/C][C]0[/C][C]2.07407407407407[/C][C]-2.07407407407407[/C][/ROW]
[ROW][C]53[/C][C]0[/C][C]7.85185185185185[/C][C]-7.85185185185185[/C][/ROW]
[ROW][C]54[/C][C]1[/C][C]0.714285714285714[/C][C]0.285714285714286[/C][/ROW]
[ROW][C]55[/C][C]1[/C][C]0.0721649484536082[/C][C]0.927835051546392[/C][/ROW]
[ROW][C]56[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]57[/C][C]0[/C][C]2.07407407407407[/C][C]-2.07407407407407[/C][/ROW]
[ROW][C]58[/C][C]0[/C][C]7.85185185185185[/C][C]-7.85185185185185[/C][/ROW]
[ROW][C]59[/C][C]0[/C][C]2.07407407407407[/C][C]-2.07407407407407[/C][/ROW]
[ROW][C]60[/C][C]0[/C][C]0.857142857142857[/C][C]-0.857142857142857[/C][/ROW]
[ROW][C]61[/C][C]0[/C][C]2.07407407407407[/C][C]-2.07407407407407[/C][/ROW]
[ROW][C]62[/C][C]0[/C][C]7.85185185185185[/C][C]-7.85185185185185[/C][/ROW]
[ROW][C]63[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]64[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]65[/C][C]0[/C][C]0.857142857142857[/C][C]-0.857142857142857[/C][/ROW]
[ROW][C]66[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]67[/C][C]0[/C][C]2.07407407407407[/C][C]-2.07407407407407[/C][/ROW]
[ROW][C]68[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]69[/C][C]0[/C][C]0.857142857142857[/C][C]-0.857142857142857[/C][/ROW]
[ROW][C]70[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]71[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]72[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]73[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]74[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]75[/C][C]0[/C][C]2.07407407407407[/C][C]-2.07407407407407[/C][/ROW]
[ROW][C]76[/C][C]0[/C][C]0.714285714285714[/C][C]-0.714285714285714[/C][/ROW]
[ROW][C]77[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]78[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]79[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]80[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]81[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]82[/C][C]0[/C][C]2.07407407407407[/C][C]-2.07407407407407[/C][/ROW]
[ROW][C]83[/C][C]0[/C][C]7.85185185185185[/C][C]-7.85185185185185[/C][/ROW]
[ROW][C]84[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]85[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]86[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]87[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]88[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]89[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]90[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]91[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]92[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]93[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]94[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]95[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]96[/C][C]0[/C][C]0.857142857142857[/C][C]-0.857142857142857[/C][/ROW]
[ROW][C]97[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]98[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]99[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]100[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]101[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]102[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]103[/C][C]0[/C][C]7.85185185185185[/C][C]-7.85185185185185[/C][/ROW]
[ROW][C]104[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]105[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]106[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]107[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]108[/C][C]0[/C][C]0.857142857142857[/C][C]-0.857142857142857[/C][/ROW]
[ROW][C]109[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]110[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]111[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]112[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]113[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]114[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]115[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]116[/C][C]0[/C][C]2.07407407407407[/C][C]-2.07407407407407[/C][/ROW]
[ROW][C]117[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]118[/C][C]0[/C][C]2.07407407407407[/C][C]-2.07407407407407[/C][/ROW]
[ROW][C]119[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]120[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]121[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]122[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]123[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]124[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]125[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]126[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]127[/C][C]0[/C][C]0.857142857142857[/C][C]-0.857142857142857[/C][/ROW]
[ROW][C]128[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]129[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]130[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]131[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]132[/C][C]0[/C][C]0.857142857142857[/C][C]-0.857142857142857[/C][/ROW]
[ROW][C]133[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]134[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]135[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]136[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]137[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]138[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]139[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]140[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]141[/C][C]0[/C][C]7.85185185185185[/C][C]-7.85185185185185[/C][/ROW]
[ROW][C]142[/C][C]0[/C][C]7.85185185185185[/C][C]-7.85185185185185[/C][/ROW]
[ROW][C]143[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]144[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]145[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]146[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]147[/C][C]0[/C][C]7.85185185185185[/C][C]-7.85185185185185[/C][/ROW]
[ROW][C]148[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]149[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]150[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]151[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]152[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]153[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]154[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]155[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]156[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]157[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]158[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]159[/C][C]0[/C][C]0.714285714285714[/C][C]-0.714285714285714[/C][/ROW]
[ROW][C]160[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]161[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]162[/C][C]0[/C][C]0.714285714285714[/C][C]-0.714285714285714[/C][/ROW]
[ROW][C]163[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]164[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]165[/C][C]0[/C][C]0.857142857142857[/C][C]-0.857142857142857[/C][/ROW]
[ROW][C]166[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]167[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]168[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]169[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]170[/C][C]0[/C][C]7.85185185185185[/C][C]-7.85185185185185[/C][/ROW]
[ROW][C]171[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[ROW][C]172[/C][C]0[/C][C]0.0721649484536082[/C][C]-0.0721649484536082[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=200541&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=200541&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	46	7.85185185185185	38.1481481481481
2	38	7.85185185185185	30.1481481481481
3	24	7.85185185185185	16.1481481481481
4	29	7.85185185185185	21.1481481481481
5	11	7.85185185185185	3.14814814814815
6	11	7.85185185185185	3.14814814814815
7	13	7.85185185185185	5.14814814814815
8	7	7.85185185185185	-0.851851851851852
9	7	2.07407407407407	4.92592592592593
10	8	7.85185185185185	0.148148148148148
11	8	2.07407407407407	5.92592592592593
12	6	2.07407407407407	3.92592592592593
13	6	7.85185185185185	-1.85185185185185
14	7	2.07407407407407	4.92592592592593
15	6	2.07407407407407	3.92592592592593
16	3	7.85185185185185	-4.85185185185185
17	3	7.85185185185185	-4.85185185185185
18	4	7.85185185185185	-3.85185185185185
19	4	0.857142857142857	3.14285714285714
20	4	2.07407407407407	1.92592592592593
21	1	2.07407407407407	-1.07407407407407
22	2	0.857142857142857	1.14285714285714
23	2	0.714285714285714	1.28571428571429
24	2	2.07407407407407	-0.074074074074074
25	2	2.07407407407407	-0.074074074074074
26	2	0.0721649484536082	1.92783505154639
27	3	7.85185185185185	-4.85185185185185
28	2	2.07407407407407	-0.074074074074074
29	3	7.85185185185185	-4.85185185185185
30	3	0.857142857142857	2.14285714285714
31	1	2.07407407407407	-1.07407407407407
32	1	0.714285714285714	0.285714285714286
33	2	7.85185185185185	-5.85185185185185
34	1	2.07407407407407	-1.07407407407407
35	2	2.07407407407407	-0.074074074074074
36	1	7.85185185185185	-6.85185185185185
37	2	2.07407407407407	-0.074074074074074
38	2	2.07407407407407	-0.074074074074074
39	1	2.07407407407407	-1.07407407407407
40	1	0.857142857142857	0.142857142857143
41	1	0.857142857142857	0.142857142857143
42	1	2.07407407407407	-1.07407407407407
43	0	7.85185185185185	-7.85185185185185
44	1	0.0721649484536082	0.927835051546392
45	1	0.0721649484536082	0.927835051546392
46	1	0.0721649484536082	0.927835051546392
47	1	0.0721649484536082	0.927835051546392
48	0	0.0721649484536082	-0.0721649484536082
49	1	2.07407407407407	-1.07407407407407
50	1	0.714285714285714	0.285714285714286
51	1	0.857142857142857	0.142857142857143
52	0	2.07407407407407	-2.07407407407407
53	0	7.85185185185185	-7.85185185185185
54	1	0.714285714285714	0.285714285714286
55	1	0.0721649484536082	0.927835051546392
56	0	0.0721649484536082	-0.0721649484536082
57	0	2.07407407407407	-2.07407407407407
58	0	7.85185185185185	-7.85185185185185
59	0	2.07407407407407	-2.07407407407407
60	0	0.857142857142857	-0.857142857142857
61	0	2.07407407407407	-2.07407407407407
62	0	7.85185185185185	-7.85185185185185
63	0	0.0721649484536082	-0.0721649484536082
64	0	0.0721649484536082	-0.0721649484536082
65	0	0.857142857142857	-0.857142857142857
66	0	0.0721649484536082	-0.0721649484536082
67	0	2.07407407407407	-2.07407407407407
68	0	0.0721649484536082	-0.0721649484536082
69	0	0.857142857142857	-0.857142857142857
70	0	0.0721649484536082	-0.0721649484536082
71	0	0.0721649484536082	-0.0721649484536082
72	0	0.0721649484536082	-0.0721649484536082
73	0	0.0721649484536082	-0.0721649484536082
74	0	0.0721649484536082	-0.0721649484536082
75	0	2.07407407407407	-2.07407407407407
76	0	0.714285714285714	-0.714285714285714
77	0	0.0721649484536082	-0.0721649484536082
78	0	0.0721649484536082	-0.0721649484536082
79	0	0.0721649484536082	-0.0721649484536082
80	0	0.0721649484536082	-0.0721649484536082
81	0	0.0721649484536082	-0.0721649484536082
82	0	2.07407407407407	-2.07407407407407
83	0	7.85185185185185	-7.85185185185185
84	0	0.0721649484536082	-0.0721649484536082
85	0	0.0721649484536082	-0.0721649484536082
86	0	0.0721649484536082	-0.0721649484536082
87	0	0.0721649484536082	-0.0721649484536082
88	0	0.0721649484536082	-0.0721649484536082
89	0	0.0721649484536082	-0.0721649484536082
90	0	0.0721649484536082	-0.0721649484536082
91	0	0.0721649484536082	-0.0721649484536082
92	0	0.0721649484536082	-0.0721649484536082
93	0	0.0721649484536082	-0.0721649484536082
94	0	0.0721649484536082	-0.0721649484536082
95	0	0.0721649484536082	-0.0721649484536082
96	0	0.857142857142857	-0.857142857142857
97	0	0.0721649484536082	-0.0721649484536082
98	0	0.0721649484536082	-0.0721649484536082
99	0	0.0721649484536082	-0.0721649484536082
100	0	0.0721649484536082	-0.0721649484536082
101	0	0.0721649484536082	-0.0721649484536082
102	0	0.0721649484536082	-0.0721649484536082
103	0	7.85185185185185	-7.85185185185185
104	0	0.0721649484536082	-0.0721649484536082
105	0	0.0721649484536082	-0.0721649484536082
106	0	0.0721649484536082	-0.0721649484536082
107	0	0.0721649484536082	-0.0721649484536082
108	0	0.857142857142857	-0.857142857142857
109	0	0.0721649484536082	-0.0721649484536082
110	0	0.0721649484536082	-0.0721649484536082
111	0	0.0721649484536082	-0.0721649484536082
112	0	0.0721649484536082	-0.0721649484536082
113	0	0.0721649484536082	-0.0721649484536082
114	0	0.0721649484536082	-0.0721649484536082
115	0	0.0721649484536082	-0.0721649484536082
116	0	2.07407407407407	-2.07407407407407
117	0	0.0721649484536082	-0.0721649484536082
118	0	2.07407407407407	-2.07407407407407
119	0	0.0721649484536082	-0.0721649484536082
120	0	0.0721649484536082	-0.0721649484536082
121	0	0.0721649484536082	-0.0721649484536082
122	0	0.0721649484536082	-0.0721649484536082
123	0	0.0721649484536082	-0.0721649484536082
124	0	0.0721649484536082	-0.0721649484536082
125	0	0.0721649484536082	-0.0721649484536082
126	0	0.0721649484536082	-0.0721649484536082
127	0	0.857142857142857	-0.857142857142857
128	0	0.0721649484536082	-0.0721649484536082
129	0	0.0721649484536082	-0.0721649484536082
130	0	0.0721649484536082	-0.0721649484536082
131	0	0.0721649484536082	-0.0721649484536082
132	0	0.857142857142857	-0.857142857142857
133	0	0.0721649484536082	-0.0721649484536082
134	0	0.0721649484536082	-0.0721649484536082
135	0	0.0721649484536082	-0.0721649484536082
136	0	0.0721649484536082	-0.0721649484536082
137	0	0.0721649484536082	-0.0721649484536082
138	0	0.0721649484536082	-0.0721649484536082
139	0	0.0721649484536082	-0.0721649484536082
140	0	0.0721649484536082	-0.0721649484536082
141	0	7.85185185185185	-7.85185185185185
142	0	7.85185185185185	-7.85185185185185
143	0	0.0721649484536082	-0.0721649484536082
144	0	0.0721649484536082	-0.0721649484536082
145	0	0.0721649484536082	-0.0721649484536082
146	0	0.0721649484536082	-0.0721649484536082
147	0	7.85185185185185	-7.85185185185185
148	0	0.0721649484536082	-0.0721649484536082
149	0	0.0721649484536082	-0.0721649484536082
150	0	0.0721649484536082	-0.0721649484536082
151	0	0.0721649484536082	-0.0721649484536082
152	0	0.0721649484536082	-0.0721649484536082
153	0	0.0721649484536082	-0.0721649484536082
154	0	0.0721649484536082	-0.0721649484536082
155	0	0.0721649484536082	-0.0721649484536082
156	0	0.0721649484536082	-0.0721649484536082
157	0	0.0721649484536082	-0.0721649484536082
158	0	0.0721649484536082	-0.0721649484536082
159	0	0.714285714285714	-0.714285714285714
160	0	0.0721649484536082	-0.0721649484536082
161	0	0.0721649484536082	-0.0721649484536082
162	0	0.714285714285714	-0.714285714285714
163	0	0.0721649484536082	-0.0721649484536082
164	0	0.0721649484536082	-0.0721649484536082
165	0	0.857142857142857	-0.857142857142857
166	0	0.0721649484536082	-0.0721649484536082
167	0	0.0721649484536082	-0.0721649484536082
168	0	0.0721649484536082	-0.0721649484536082
169	0	0.0721649484536082	-0.0721649484536082
170	0	7.85185185185185	-7.85185185185185
171	0	0.0721649484536082	-0.0721649484536082
172	0	0.0721649484536082	-0.0721649484536082

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