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Author*The author of this computation has been verified*
R Software Modulerwasp_pairs.wasp
Title produced by softwareKendall tau Correlation Matrix
Date of computationWed, 21 Dec 2011 09:57:54 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Dec/21/t1324479498wncb8fg82zkalqz.htm/, Retrieved Tue, 07 May 2024 23:36:40 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=158794, Retrieved Tue, 07 May 2024 23:36:40 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact58
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 14:57:54] [0d30dc567117fe0fee498f56087c946c] [Current]
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Dataseries X:
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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=158794&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]2 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=158794&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=158794&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net







Correlations for all pairs of data series (method=kendall)
LFMPVTimeCVBlogslogins
LFM10.5190.5920.2680.5730.449
PV0.51910.7390.4630.6270.661
Time0.5920.73910.3440.6830.609
CV0.2680.4630.34410.2890.379
Blogs0.5730.6270.6830.28910.523
logins0.4490.6610.6090.3790.5231

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=kendall) \tabularnewline
  & LFM & PV & Time & CV & Blogs & logins \tabularnewline
LFM & 1 & 0.519 & 0.592 & 0.268 & 0.573 & 0.449 \tabularnewline
PV & 0.519 & 1 & 0.739 & 0.463 & 0.627 & 0.661 \tabularnewline
Time & 0.592 & 0.739 & 1 & 0.344 & 0.683 & 0.609 \tabularnewline
CV & 0.268 & 0.463 & 0.344 & 1 & 0.289 & 0.379 \tabularnewline
Blogs & 0.573 & 0.627 & 0.683 & 0.289 & 1 & 0.523 \tabularnewline
logins & 0.449 & 0.661 & 0.609 & 0.379 & 0.523 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=158794&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=kendall)[/C][/ROW]
[ROW][C] [/C][C]LFM[/C][C]PV[/C][C]Time[/C][C]CV[/C][C]Blogs[/C][C]logins[/C][/ROW]
[ROW][C]LFM[/C][C]1[/C][C]0.519[/C][C]0.592[/C][C]0.268[/C][C]0.573[/C][C]0.449[/C][/ROW]
[ROW][C]PV[/C][C]0.519[/C][C]1[/C][C]0.739[/C][C]0.463[/C][C]0.627[/C][C]0.661[/C][/ROW]
[ROW][C]Time[/C][C]0.592[/C][C]0.739[/C][C]1[/C][C]0.344[/C][C]0.683[/C][C]0.609[/C][/ROW]
[ROW][C]CV[/C][C]0.268[/C][C]0.463[/C][C]0.344[/C][C]1[/C][C]0.289[/C][C]0.379[/C][/ROW]
[ROW][C]Blogs[/C][C]0.573[/C][C]0.627[/C][C]0.683[/C][C]0.289[/C][C]1[/C][C]0.523[/C][/ROW]
[ROW][C]logins[/C][C]0.449[/C][C]0.661[/C][C]0.609[/C][C]0.379[/C][C]0.523[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=158794&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=158794&T=1

As an alternative you can also use a QR Code:  

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

Correlations for all pairs of data series (method=kendall)
LFMPVTimeCVBlogslogins
LFM10.5190.5920.2680.5730.449
PV0.51910.7390.4630.6270.661
Time0.5920.73910.3440.6830.609
CV0.2680.4630.34410.2890.379
Blogs0.5730.6270.6830.28910.523
logins0.4490.6610.6090.3790.5231







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
LFM;PV0.66430.71290.5187
p-value(0)(0)(0)
LFM;Time0.76350.79660.5916
p-value(0)(0)(0)
LFM;CV0.25470.38020.2682
p-value(0)(0)(0)
LFM;Blogs0.76760.77670.573
p-value(0)(0)(0)
LFM;logins0.55260.62880.4486
p-value(0)(0)(0)
PV;Time0.89280.90250.7387
p-value(0)(0)(0)
PV;CV0.56330.63320.4628
p-value(0)(0)(0)
PV;Blogs0.76060.82490.6272
p-value(0)(0)(0)
PV;logins0.75880.8450.6609
p-value(0)(0)(0)
Time;CV0.39030.4890.3435
p-value(0)(0)(0)
Time;Blogs0.83090.87170.683
p-value(0)(0)(0)
Time;logins0.7160.79820.609
p-value(0)(0)(0)
CV;Blogs0.22890.41730.2892
p-value(1e-04)(0)(0)
CV;logins0.38820.52260.3788
p-value(0)(0)(0)
Blogs;logins0.56610.71780.523
p-value(0)(0)(0)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
LFM;PV & 0.6643 & 0.7129 & 0.5187 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
LFM;Time & 0.7635 & 0.7966 & 0.5916 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
LFM;CV & 0.2547 & 0.3802 & 0.2682 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
LFM;Blogs & 0.7676 & 0.7767 & 0.573 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
LFM;logins & 0.5526 & 0.6288 & 0.4486 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
PV;Time & 0.8928 & 0.9025 & 0.7387 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
PV;CV & 0.5633 & 0.6332 & 0.4628 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
PV;Blogs & 0.7606 & 0.8249 & 0.6272 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
PV;logins & 0.7588 & 0.845 & 0.6609 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Time;CV & 0.3903 & 0.489 & 0.3435 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Time;Blogs & 0.8309 & 0.8717 & 0.683 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Time;logins & 0.716 & 0.7982 & 0.609 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
CV;Blogs & 0.2289 & 0.4173 & 0.2892 \tabularnewline
p-value & (1e-04) & (0) & (0) \tabularnewline
CV;logins & 0.3882 & 0.5226 & 0.3788 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Blogs;logins & 0.5661 & 0.7178 & 0.523 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=158794&T=2

[TABLE]
[ROW][C]Correlations for all pairs of data series with p-values[/C][/ROW]
[ROW][C]pair[/C][C]Pearson r[/C][C]Spearman rho[/C][C]Kendall tau[/C][/ROW]
[ROW][C]LFM;PV[/C][C]0.6643[/C][C]0.7129[/C][C]0.5187[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]LFM;Time[/C][C]0.7635[/C][C]0.7966[/C][C]0.5916[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]LFM;CV[/C][C]0.2547[/C][C]0.3802[/C][C]0.2682[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]LFM;Blogs[/C][C]0.7676[/C][C]0.7767[/C][C]0.573[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]LFM;logins[/C][C]0.5526[/C][C]0.6288[/C][C]0.4486[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]PV;Time[/C][C]0.8928[/C][C]0.9025[/C][C]0.7387[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]PV;CV[/C][C]0.5633[/C][C]0.6332[/C][C]0.4628[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]PV;Blogs[/C][C]0.7606[/C][C]0.8249[/C][C]0.6272[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]PV;logins[/C][C]0.7588[/C][C]0.845[/C][C]0.6609[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Time;CV[/C][C]0.3903[/C][C]0.489[/C][C]0.3435[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Time;Blogs[/C][C]0.8309[/C][C]0.8717[/C][C]0.683[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Time;logins[/C][C]0.716[/C][C]0.7982[/C][C]0.609[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]CV;Blogs[/C][C]0.2289[/C][C]0.4173[/C][C]0.2892[/C][/ROW]
[ROW][C]p-value[/C][C](1e-04)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]CV;logins[/C][C]0.3882[/C][C]0.5226[/C][C]0.3788[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Blogs;logins[/C][C]0.5661[/C][C]0.7178[/C][C]0.523[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=158794&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=158794&T=2

As an alternative you can also use a QR Code:  

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

Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
LFM;PV0.66430.71290.5187
p-value(0)(0)(0)
LFM;Time0.76350.79660.5916
p-value(0)(0)(0)
LFM;CV0.25470.38020.2682
p-value(0)(0)(0)
LFM;Blogs0.76760.77670.573
p-value(0)(0)(0)
LFM;logins0.55260.62880.4486
p-value(0)(0)(0)
PV;Time0.89280.90250.7387
p-value(0)(0)(0)
PV;CV0.56330.63320.4628
p-value(0)(0)(0)
PV;Blogs0.76060.82490.6272
p-value(0)(0)(0)
PV;logins0.75880.8450.6609
p-value(0)(0)(0)
Time;CV0.39030.4890.3435
p-value(0)(0)(0)
Time;Blogs0.83090.87170.683
p-value(0)(0)(0)
Time;logins0.7160.79820.609
p-value(0)(0)(0)
CV;Blogs0.22890.41730.2892
p-value(1e-04)(0)(0)
CV;logins0.38820.52260.3788
p-value(0)(0)(0)
Blogs;logins0.56610.71780.523
p-value(0)(0)(0)



Parameters (Session):
par1 = kendall ;
Parameters (R input):
par1 = kendall ;
R code (references can be found in the software module):
panel.tau <- function(x, y, digits=2, prefix='', cex.cor)
{
usr <- par('usr'); on.exit(par(usr))
par(usr = c(0, 1, 0, 1))
rr <- cor.test(x, y, method=par1)
r <- round(rr$p.value,2)
txt <- format(c(r, 0.123456789), digits=digits)[1]
txt <- paste(prefix, txt, sep='')
if(missing(cex.cor)) cex <- 0.5/strwidth(txt)
text(0.5, 0.5, txt, cex = cex)
}
panel.hist <- function(x, ...)
{
usr <- par('usr'); on.exit(par(usr))
par(usr = c(usr[1:2], 0, 1.5) )
h <- hist(x, plot = FALSE)
breaks <- h$breaks; nB <- length(breaks)
y <- h$counts; y <- y/max(y)
rect(breaks[-nB], 0, breaks[-1], y, col='grey', ...)
}
bitmap(file='test1.png')
pairs(t(y),diag.panel=panel.hist, upper.panel=panel.smooth, lower.panel=panel.tau, main=main)
dev.off()
load(file='createtable')
n <- length(y[,1])
n
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,paste('Correlations for all pairs of data series (method=',par1,')',sep=''),n+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,' ',header=TRUE)
for (i in 1:n) {
a<-table.element(a,dimnames(t(x))[[2]][i],header=TRUE)
}
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,dimnames(t(x))[[2]][i],header=TRUE)
for (j in 1:n) {
r <- cor.test(y[i,],y[j,],method=par1)
a<-table.element(a,round(r$estimate,3))
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Correlations for all pairs of data series with p-values',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'pair',1,TRUE)
a<-table.element(a,'Pearson r',1,TRUE)
a<-table.element(a,'Spearman rho',1,TRUE)
a<-table.element(a,'Kendall tau',1,TRUE)
a<-table.row.end(a)
cor.test(y[1,],y[2,],method=par1)
for (i in 1:(n-1))
{
for (j in (i+1):n)
{
a<-table.row.start(a)
dum <- paste(dimnames(t(x))[[2]][i],';',dimnames(t(x))[[2]][j],sep='')
a<-table.element(a,dum,header=TRUE)
rp <- cor.test(y[i,],y[j,],method='pearson')
a<-table.element(a,round(rp$estimate,4))
rs <- cor.test(y[i,],y[j,],method='spearman')
a<-table.element(a,round(rs$estimate,4))
rk <- cor.test(y[i,],y[j,],method='kendall')
a<-table.element(a,round(rk$estimate,4))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value',header=T)
a<-table.element(a,paste('(',round(rp$p.value,4),')',sep=''))
a<-table.element(a,paste('(',round(rs$p.value,4),')',sep=''))
a<-table.element(a,paste('(',round(rk$p.value,4),')',sep=''))
a<-table.row.end(a)
}
}
a<-table.end(a)
table.save(a,file='mytable1.tab')