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Author's title

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 15:11:45 -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/t13244983303aafa2tjnly9f1u.htm/, Retrieved Tue, 07 May 2024 21:59:57 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=158980, Retrieved Tue, 07 May 2024 21:59:57 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact87
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Recursive Partitioning (Regression Trees)] [Regression Tree] [2011-12-21 18:18:15] [489eb911c8db04aca1fc54d886fc3144]
- RMP     [Kendall tau Correlation Matrix] [Pearson Correlati...] [2011-12-21 20:11:45] [d160b678fd2d7bb562db2147d7efddc2] [Current]
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Dataseries X:
210907	56	3	79	30	112285
120982	56	4	58	28	84786
176508	54	12	60	38	83123
179321	89	2	108	30	101193
123185	40	1	49	22	38361
52746	25	3	0	26	68504
385534	92	0	121	25	119182
33170	18	0	1	18	22807
101645	63	0	20	11	17140
149061	44	5	43	26	116174
165446	33	0	69	25	57635
237213	84	0	78	38	66198
173326	88	7	86	44	71701
133131	55	7	44	30	57793
258873	60	3	104	40	80444
180083	66	9	63	34	53855
324799	154	0	158	47	97668
230964	53	4	102	30	133824
236785	119	3	77	31	101481
135473	41	0	82	23	99645
202925	61	7	115	36	114789
215147	58	0	101	36	99052
344297	75	1	80	30	67654
153935	33	5	50	25	65553
132943	40	7	83	39	97500
174724	92	0	123	34	69112
174415	100	0	73	31	82753
225548	112	5	81	31	85323
223632	73	0	105	33	72654
124817	40	0	47	25	30727
221698	45	0	105	33	77873
210767	60	3	94	35	117478
170266	62	4	44	42	74007
260561	75	1	114	43	90183
84853	31	4	38	30	61542
294424	77	2	107	33	101494
101011	34	0	30	13	27570
215641	46	0	71	32	55813
325107	99	0	84	36	79215
7176	17	0	0	0	1423
167542	66	2	59	28	55461
106408	30	1	33	14	31081
96560	76	0	42	17	22996
265769	146	2	96	32	83122
269651	67	10	106	30	70106
149112	56	6	56	35	60578
175824	107	0	57	20	39992
152871	58	5	59	28	79892
111665	34	4	39	28	49810
116408	61	1	34	39	71570
362301	119	2	76	34	100708
78800	42	2	20	26	33032
183167	66	0	91	39	82875
277965	89	8	115	39	139077
150629	44	3	85	33	71595
168809	66	0	76	28	72260
24188	24	0	8	4	5950
329267	259	8	79	39	115762
65029	17	5	21	18	32551
101097	64	3	30	14	31701
218946	41	1	76	29	80670
244052	68	5	101	44	143558
341570	168	1	94	21	117105
103597	43	1	27	16	23789
233328	132	5	92	28	120733
256462	105	0	123	35	105195
206161	71	12	75	28	73107
311473	112	8	128	38	132068
235800	94	8	105	23	149193
177939	82	8	55	36	46821
207176	70	8	56	32	87011
196553	57	2	41	29	95260
174184	53	0	72	25	55183
143246	103	5	67	27	106671
187559	121	8	75	36	73511
187681	62	2	114	28	92945
119016	52	5	118	23	78664
182192	52	12	77	40	70054
73566	32	6	22	23	22618
194979	62	7	66	40	74011
167488	45	2	69	28	83737
143756	46	0	105	34	69094
275541	63	4	116	33	93133
243199	75	3	88	28	95536
182999	88	6	73	34	225920
135649	46	2	99	30	62133
152299	53	0	62	33	61370
120221	37	1	53	22	43836
346485	90	0	118	38	106117
145790	63	5	30	26	38692
193339	78	2	100	35	84651
80953	25	0	49	8	56622
122774	45	0	24	24	15986
130585	46	5	67	29	95364
112611	41	0	46	20	26706
286468	144	1	57	29	89691
241066	82	0	75	45	67267
148446	91	1	135	37	126846
204713	71	1	68	33	41140
182079	63	2	124	33	102860
140344	53	6	33	25	51715
220516	62	1	98	32	55801
243060	63	4	58	29	111813
162765	32	2	68	28	120293
182613	39	3	81	28	138599
232138	62	0	131	31	161647
265318	117	10	110	52	115929
85574	34	0	37	21	24266
310839	92	9	130	24	162901
225060	93	7	93	41	109825
232317	54	0	118	33	129838
144966	144	0	39	32	37510
43287	14	4	13	19	43750
155754	61	4	74	20	40652
164709	109	0	81	31	87771
201940	38	0	109	31	85872
235454	73	0	151	32	89275
220801	75	1	51	18	44418
99466	50	0	28	23	192565
92661	61	1	40	17	35232
133328	55	0	56	20	40909
61361	77	0	27	12	13294
125930	75	4	37	17	32387
100750	72	0	83	30	140867
224549	50	4	54	31	120662
82316	32	4	27	10	21233
102010	53	3	28	13	44332




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'AstonUniversity' @ aston.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 & 'AstonUniversity' @ aston.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=158980&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]'AstonUniversity' @ aston.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=158980&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=158980&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'AstonUniversity' @ aston.wessa.net







Correlations for all pairs of data series (method=pearson)
Tijd_RFCLoginsShared_Compendiums#BlogsCompendiums_reviewedTotale_tijd_Compendiums
Tijd_RFC10.6370.130.7230.5940.56
Logins0.63710.130.4180.4010.351
Shared_Compendiums0.130.1310.0540.2960.231
#Blogs0.7230.4180.05410.6140.621
Compendiums_reviewed0.5940.4010.2960.61410.51
Totale_tijd_Compendiums0.560.3510.2310.6210.511

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & Tijd_RFC & Logins & Shared_Compendiums & #Blogs & Compendiums_reviewed & Totale_tijd_Compendiums \tabularnewline
Tijd_RFC & 1 & 0.637 & 0.13 & 0.723 & 0.594 & 0.56 \tabularnewline
Logins & 0.637 & 1 & 0.13 & 0.418 & 0.401 & 0.351 \tabularnewline
Shared_Compendiums & 0.13 & 0.13 & 1 & 0.054 & 0.296 & 0.231 \tabularnewline
#Blogs & 0.723 & 0.418 & 0.054 & 1 & 0.614 & 0.621 \tabularnewline
Compendiums_reviewed & 0.594 & 0.401 & 0.296 & 0.614 & 1 & 0.51 \tabularnewline
Totale_tijd_Compendiums & 0.56 & 0.351 & 0.231 & 0.621 & 0.51 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=158980&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]Tijd_RFC[/C][C]Logins[/C][C]Shared_Compendiums[/C][C]#Blogs[/C][C]Compendiums_reviewed[/C][C]Totale_tijd_Compendiums[/C][/ROW]
[ROW][C]Tijd_RFC[/C][C]1[/C][C]0.637[/C][C]0.13[/C][C]0.723[/C][C]0.594[/C][C]0.56[/C][/ROW]
[ROW][C]Logins[/C][C]0.637[/C][C]1[/C][C]0.13[/C][C]0.418[/C][C]0.401[/C][C]0.351[/C][/ROW]
[ROW][C]Shared_Compendiums[/C][C]0.13[/C][C]0.13[/C][C]1[/C][C]0.054[/C][C]0.296[/C][C]0.231[/C][/ROW]
[ROW][C]#Blogs[/C][C]0.723[/C][C]0.418[/C][C]0.054[/C][C]1[/C][C]0.614[/C][C]0.621[/C][/ROW]
[ROW][C]Compendiums_reviewed[/C][C]0.594[/C][C]0.401[/C][C]0.296[/C][C]0.614[/C][C]1[/C][C]0.51[/C][/ROW]
[ROW][C]Totale_tijd_Compendiums[/C][C]0.56[/C][C]0.351[/C][C]0.231[/C][C]0.621[/C][C]0.51[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=158980&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=158980&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=pearson)
Tijd_RFCLoginsShared_Compendiums#BlogsCompendiums_reviewedTotale_tijd_Compendiums
Tijd_RFC10.6370.130.7230.5940.56
Logins0.63710.130.4180.4010.351
Shared_Compendiums0.130.1310.0540.2960.231
#Blogs0.7230.4180.05410.6140.621
Compendiums_reviewed0.5940.4010.2960.61410.51
Totale_tijd_Compendiums0.560.3510.2310.6210.511







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
Tijd_RFC;Logins0.63740.65540.484
p-value(0)(0)(0)
Tijd_RFC;Shared_Compendiums0.12980.13330.0972
p-value(0.1457)(0.135)(0.1284)
Tijd_RFC;#Blogs0.72330.73960.5671
p-value(0)(0)(0)
Tijd_RFC;Compendiums_reviewed0.59390.60430.4398
p-value(0)(0)(0)
Tijd_RFC;Totale_tijd_Compendiums0.56010.64030.4721
p-value(0)(0)(0)
Logins;Shared_Compendiums0.12970.09590.0674
p-value(0.1462)(0.2837)(0.2946)
Logins;#Blogs0.41770.49750.3493
p-value(0)(0)(0)
Logins;Compendiums_reviewed0.40110.4460.3217
p-value(0)(0)(0)
Logins;Totale_tijd_Compendiums0.35110.41640.2838
p-value(1e-04)(0)(0)
Shared_Compendiums;#Blogs0.05380.02150.0182
p-value(0.5478)(0.81)(0.777)
Shared_Compendiums;Compendiums_reviewed0.29560.21460.1512
p-value(7e-04)(0.0154)(0.02)
Shared_Compendiums;Totale_tijd_Compendiums0.23090.24370.1813
p-value(0.009)(0.0058)(0.0046)
#Blogs;Compendiums_reviewed0.61350.60090.4359
p-value(0)(0)(0)
#Blogs;Totale_tijd_Compendiums0.62090.69730.5194
p-value(0)(0)(0)
Compendiums_reviewed;Totale_tijd_Compendiums0.51040.50590.3561
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
Tijd_RFC;Logins & 0.6374 & 0.6554 & 0.484 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Tijd_RFC;Shared_Compendiums & 0.1298 & 0.1333 & 0.0972 \tabularnewline
p-value & (0.1457) & (0.135) & (0.1284) \tabularnewline
Tijd_RFC;#Blogs & 0.7233 & 0.7396 & 0.5671 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Tijd_RFC;Compendiums_reviewed & 0.5939 & 0.6043 & 0.4398 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Tijd_RFC;Totale_tijd_Compendiums & 0.5601 & 0.6403 & 0.4721 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Logins;Shared_Compendiums & 0.1297 & 0.0959 & 0.0674 \tabularnewline
p-value & (0.1462) & (0.2837) & (0.2946) \tabularnewline
Logins;#Blogs & 0.4177 & 0.4975 & 0.3493 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Logins;Compendiums_reviewed & 0.4011 & 0.446 & 0.3217 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Logins;Totale_tijd_Compendiums & 0.3511 & 0.4164 & 0.2838 \tabularnewline
p-value & (1e-04) & (0) & (0) \tabularnewline
Shared_Compendiums;#Blogs & 0.0538 & 0.0215 & 0.0182 \tabularnewline
p-value & (0.5478) & (0.81) & (0.777) \tabularnewline
Shared_Compendiums;Compendiums_reviewed & 0.2956 & 0.2146 & 0.1512 \tabularnewline
p-value & (7e-04) & (0.0154) & (0.02) \tabularnewline
Shared_Compendiums;Totale_tijd_Compendiums & 0.2309 & 0.2437 & 0.1813 \tabularnewline
p-value & (0.009) & (0.0058) & (0.0046) \tabularnewline
#Blogs;Compendiums_reviewed & 0.6135 & 0.6009 & 0.4359 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
#Blogs;Totale_tijd_Compendiums & 0.6209 & 0.6973 & 0.5194 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Compendiums_reviewed;Totale_tijd_Compendiums & 0.5104 & 0.5059 & 0.3561 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=158980&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]Tijd_RFC;Logins[/C][C]0.6374[/C][C]0.6554[/C][C]0.484[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Tijd_RFC;Shared_Compendiums[/C][C]0.1298[/C][C]0.1333[/C][C]0.0972[/C][/ROW]
[ROW][C]p-value[/C][C](0.1457)[/C][C](0.135)[/C][C](0.1284)[/C][/ROW]
[ROW][C]Tijd_RFC;#Blogs[/C][C]0.7233[/C][C]0.7396[/C][C]0.5671[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Tijd_RFC;Compendiums_reviewed[/C][C]0.5939[/C][C]0.6043[/C][C]0.4398[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Tijd_RFC;Totale_tijd_Compendiums[/C][C]0.5601[/C][C]0.6403[/C][C]0.4721[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Logins;Shared_Compendiums[/C][C]0.1297[/C][C]0.0959[/C][C]0.0674[/C][/ROW]
[ROW][C]p-value[/C][C](0.1462)[/C][C](0.2837)[/C][C](0.2946)[/C][/ROW]
[ROW][C]Logins;#Blogs[/C][C]0.4177[/C][C]0.4975[/C][C]0.3493[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Logins;Compendiums_reviewed[/C][C]0.4011[/C][C]0.446[/C][C]0.3217[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Logins;Totale_tijd_Compendiums[/C][C]0.3511[/C][C]0.4164[/C][C]0.2838[/C][/ROW]
[ROW][C]p-value[/C][C](1e-04)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Shared_Compendiums;#Blogs[/C][C]0.0538[/C][C]0.0215[/C][C]0.0182[/C][/ROW]
[ROW][C]p-value[/C][C](0.5478)[/C][C](0.81)[/C][C](0.777)[/C][/ROW]
[ROW][C]Shared_Compendiums;Compendiums_reviewed[/C][C]0.2956[/C][C]0.2146[/C][C]0.1512[/C][/ROW]
[ROW][C]p-value[/C][C](7e-04)[/C][C](0.0154)[/C][C](0.02)[/C][/ROW]
[ROW][C]Shared_Compendiums;Totale_tijd_Compendiums[/C][C]0.2309[/C][C]0.2437[/C][C]0.1813[/C][/ROW]
[ROW][C]p-value[/C][C](0.009)[/C][C](0.0058)[/C][C](0.0046)[/C][/ROW]
[ROW][C]#Blogs;Compendiums_reviewed[/C][C]0.6135[/C][C]0.6009[/C][C]0.4359[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]#Blogs;Totale_tijd_Compendiums[/C][C]0.6209[/C][C]0.6973[/C][C]0.5194[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Compendiums_reviewed;Totale_tijd_Compendiums[/C][C]0.5104[/C][C]0.5059[/C][C]0.3561[/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=158980&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=158980&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
Tijd_RFC;Logins0.63740.65540.484
p-value(0)(0)(0)
Tijd_RFC;Shared_Compendiums0.12980.13330.0972
p-value(0.1457)(0.135)(0.1284)
Tijd_RFC;#Blogs0.72330.73960.5671
p-value(0)(0)(0)
Tijd_RFC;Compendiums_reviewed0.59390.60430.4398
p-value(0)(0)(0)
Tijd_RFC;Totale_tijd_Compendiums0.56010.64030.4721
p-value(0)(0)(0)
Logins;Shared_Compendiums0.12970.09590.0674
p-value(0.1462)(0.2837)(0.2946)
Logins;#Blogs0.41770.49750.3493
p-value(0)(0)(0)
Logins;Compendiums_reviewed0.40110.4460.3217
p-value(0)(0)(0)
Logins;Totale_tijd_Compendiums0.35110.41640.2838
p-value(1e-04)(0)(0)
Shared_Compendiums;#Blogs0.05380.02150.0182
p-value(0.5478)(0.81)(0.777)
Shared_Compendiums;Compendiums_reviewed0.29560.21460.1512
p-value(7e-04)(0.0154)(0.02)
Shared_Compendiums;Totale_tijd_Compendiums0.23090.24370.1813
p-value(0.009)(0.0058)(0.0046)
#Blogs;Compendiums_reviewed0.61350.60090.4359
p-value(0)(0)(0)
#Blogs;Totale_tijd_Compendiums0.62090.69730.5194
p-value(0)(0)(0)
Compendiums_reviewed;Totale_tijd_Compendiums0.51040.50590.3561
p-value(0)(0)(0)



Parameters (Session):
par1 = pearson ;
Parameters (R input):
par1 = pearson ;
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')