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Author*Unverified author*
R Software Modulerwasp_pairs.wasp
Title produced by softwareKendall tau Correlation Matrix
Date of computationFri, 07 Dec 2012 13:56:05 -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/2012/Dec/07/t13549065921twcplyaytyravg.htm/, Retrieved Thu, 28 Mar 2024 14:43:51 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=197474, Retrieved Thu, 28 Mar 2024 14:43:51 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact90
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Kendall tau Correlation Matrix] [] [2010-12-05 18:04:16] [b98453cac15ba1066b407e146608df68]
- RMPD    [Kendall tau Correlation Matrix] [Ws 10 Pearson Cor...] [2012-12-07 18:56:05] [39dab2f7d0b210f4b56642f8a91758cb] [Current]
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Dataseries X:
493	116	377	7.4	9.1	9
481	111	370	7.2	9.1	9
462	104	358	7	9	9
457	100	357	7	8.9	8.9
442	93	349	6.8	8.8	8.9
439	91	348	6.8	8.7	8.8
488	119	369	6.7	8.7	8.8
521	139	381	6.7	8.6	8.7
501	134	368	6.7	8.5	8.7
485	124	361	6.8	8.4	8.6
464	113	351	6.7	8.4	8.6
460	109	351	6.6	8.3	8.5
467	109	358	6.4	8.2	8.5
460	106	354	6.3	8.2	8.5
448	101	347	6.3	8.1	8.5
443	98	345	6.5	8.1	8.5
436	93	343	6.5	8.1	8.5
431	91	340	6.4	8.1	8.5
484	122	362	6.2	8.1	8.5
510	139	370	6.2	8.1	8.6
513	140	373	6.5	8.1	8.6
503	132	371	7	8.2	8.6
471	117	354	7.2	8.2	8.7
471	114	357	7.3	8.3	8.7
476	113	363	7.4	8.2	8.7
475	110	364	7.4	8.3	8.8
470	107	363	7.4	8.3	8.8
461	103	358	7.3	8.4	8.9
455	98	357	7.4	8.5	8.9
456	98	357	7.4	8.5	8.9
517	137	380	7.6	8.6	9
525	148	378	7.6	8.6	9
523	147	376	7.7	8.7	9
519	139	380	7.7	8.7	9
509	130	379	7.8	8.8	9
512	128	384	7.8	8.8	9
519	127	392	8	8.9	9.1
517	123	394	8.1	9	9.1
510	118	392	8.1	9	9.1
509	114	396	8.2	9	9.1
501	108	392	8.1	9	9.1
507	111	396	8.1	9.1	9.1
569	151	419	8.1	9.1	9.1
580	159	421	8.1	9	9.1
578	158	420	8.2	9.1	9.1
565	148	418	8.2	9	9.1
547	138	410	8.3	9.1	9.1
555	137	418	8.4	9.1	9.2
562	136	426	8.6	9.2	9.3
561	133	428	8.6	9.2	9.3
555	126	430	8.4	9.2	9.3
544	120	424	8	9.2	9.2
537	114	423	7.9	9.2	9.2
543	116	427	8.1	9.3	9.2
594	153	441	8.5	9.3	9.2
611	162	449	8.8	9.3	9.2
613	161	452	8.8	9.3	9.2
611	149	462	8.5	9.3	9.2
594	139	455	8.3	9.4	9.2
595	135	461	8.3	9.4	9.2
591	130	461	8.3	9.3	9.2
589	127	463	8.4	9.3	9.2
584	122	462	8.5	9.3	9.2
573	117	456	8.5	9.3	9.2
567	112	455	8.6	9.2	9.1
569	113	456	8.5	9.2	9.1
621	149	472	8.6	9.2	9
629	157	472	8.6	9.1	8.9
628	157	471	8.6	9.1	8.9
612	147	465	8.5	9.1	9
595	137	459	8.4	9.1	8.9
597	132	465	8.4	9	8.8
593	125	468	8.5	8.9	8.7
590	123	467	8.5	8.8	8.6
580	117	463	8.5	8.7	8.5
574	114	460	8.6	8.6	8.5
573	111	462	8.6	8.6	8.4
573	112	461	8.4	8.5	8.3
620	144	476	8.2	8.4	8.2
626	150	476	8	8.4	8.2
620	149	471	8	8.3	8.1
588	134	453	8	8.2	8
566	123	443	8	8.2	7.9
557	116	442	7.9	8	7.8
561	117	444	7.9	7.9	7.6
549	111	438	7.9	7.8	7.5
532	105	427	7.9	7.7	7.4
526	102	424	8	7.6	7.3
511	95	416	7.9	7.6	7.3
499	93	406	7.4	7.6	7.2
555	124	431	7.2	7.6	7.2
565	130	434	7	7.6	7.2
542	124	418	6.9	7.5	7.1
527	115	412	7.1	7.5	7
510	106	404	7.2	7.4	7
514	105	409	7.2	7.4	6.9
517	105	412	7.1	7.4	6.9
508	101	406	6.9	7.3	6.8
493	95	398	6.8	7.3	6.8
490	93	397	6.8	7.4	6.8
469	84	385	6.8	7.5	6.9
478	87	390	6.9	7.6	7
528	116	413	7.1	7.6	7
534	120	413	7.2	7.7	7.1
518	117	401	7.2	7.7	7.2
506	109	397	7.1	7.9	7.3
502	105	397	7.1	8.1	7.5
516	107	409	7.2	8.4	7.7
528	109	419	7.5	8.7	8.1
533	109	424	7.7	9	8.4
536	108	428	7.8	9.3	8.6
537	107	430	7.7	9.4	8.8
524	99	424	7.7	9.5	8.9
536	103	433	7.8	9.6	9.1
587	131	456	8	9.8	9.2
597	137	459	8.1	9.8	9.3
581	135	446	8.1	9.9	9.4
564	124	441	8	10	9.4
558	118	439	8.1	10	9.5
575	121	454	8.2	10.1	9.5
580	121	460	8.4	10.1	9.7
575	118	457	8.5	10.1	9.7
563	113	451	8.5	10.1	9.7
552	107	444	8.5	10.2	9.7
537	100	437	8.5	10.2	9.7
545	102	443	8.5	10.1	9.6
601	130	471	8.4	10.1	9.6
604	136	469	8.3	10.1	9.6
586	133	454	8.2	10.1	9.6
564	120	444	8.1	10.1	9.6
549	112	436	7.9	10.1	9.6
551	109	442	7.6	10.1	9.6
556	110	446	7.3	10	9.5
548	106	442	7.1	9.9	9.5
540	102	438	7	9.9	9.4
531	98	433	7.1	9.9	9.4
521	92	428	7.1	9.9	9.5
519	92	426	7.1	10	9.5
572	120	452	7.3	10.1	9.6
581	127	455	7.3	10.2	9.7
563	124	439	7.3	10.3	9.8
548	114	434	7.2	10.5	9.9
539	108	431	7.2	10.6	10
541	106	435	7.1	10.7	10
562	111	450	7.1	10.8	10.1




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.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 & 3 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197474&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197474&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197474&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 time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net







Correlations for all pairs of data series (method=kendall)
Totaal_werklozenJonger_dan_25_jaarVanaf_25_jaarBelgieEurogebiedEU_27
Totaal_werklozen10.4940.8060.5660.3230.258
Jonger_dan_25_jaar0.49410.2940.3530.1340.15
Vanaf_25_jaar0.8060.29410.540.3450.264
Belgie0.5660.3530.5410.3350.306
Eurogebied0.3230.1340.3450.33510.851
EU_270.2580.150.2640.3060.8511

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=kendall) \tabularnewline
  & Totaal_werklozen & Jonger_dan_25_jaar & Vanaf_25_jaar & Belgie & Eurogebied & EU_27 \tabularnewline
Totaal_werklozen & 1 & 0.494 & 0.806 & 0.566 & 0.323 & 0.258 \tabularnewline
Jonger_dan_25_jaar & 0.494 & 1 & 0.294 & 0.353 & 0.134 & 0.15 \tabularnewline
Vanaf_25_jaar & 0.806 & 0.294 & 1 & 0.54 & 0.345 & 0.264 \tabularnewline
Belgie & 0.566 & 0.353 & 0.54 & 1 & 0.335 & 0.306 \tabularnewline
Eurogebied & 0.323 & 0.134 & 0.345 & 0.335 & 1 & 0.851 \tabularnewline
EU_27 & 0.258 & 0.15 & 0.264 & 0.306 & 0.851 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197474&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=kendall)[/C][/ROW]
[ROW][C] [/C][C]Totaal_werklozen[/C][C]Jonger_dan_25_jaar[/C][C]Vanaf_25_jaar[/C][C]Belgie[/C][C]Eurogebied[/C][C]EU_27[/C][/ROW]
[ROW][C]Totaal_werklozen[/C][C]1[/C][C]0.494[/C][C]0.806[/C][C]0.566[/C][C]0.323[/C][C]0.258[/C][/ROW]
[ROW][C]Jonger_dan_25_jaar[/C][C]0.494[/C][C]1[/C][C]0.294[/C][C]0.353[/C][C]0.134[/C][C]0.15[/C][/ROW]
[ROW][C]Vanaf_25_jaar[/C][C]0.806[/C][C]0.294[/C][C]1[/C][C]0.54[/C][C]0.345[/C][C]0.264[/C][/ROW]
[ROW][C]Belgie[/C][C]0.566[/C][C]0.353[/C][C]0.54[/C][C]1[/C][C]0.335[/C][C]0.306[/C][/ROW]
[ROW][C]Eurogebied[/C][C]0.323[/C][C]0.134[/C][C]0.345[/C][C]0.335[/C][C]1[/C][C]0.851[/C][/ROW]
[ROW][C]EU_27[/C][C]0.258[/C][C]0.15[/C][C]0.264[/C][C]0.306[/C][C]0.851[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=197474&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197474&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)
Totaal_werklozenJonger_dan_25_jaarVanaf_25_jaarBelgieEurogebiedEU_27
Totaal_werklozen10.4940.8060.5660.3230.258
Jonger_dan_25_jaar0.49410.2940.3530.1340.15
Vanaf_25_jaar0.8060.29410.540.3450.264
Belgie0.5660.3530.5410.3350.306
Eurogebied0.3230.1340.3450.33510.851
EU_270.2580.150.2640.3060.8511







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
Totaal_werklozen;Jonger_dan_25_jaar0.67140.65420.4938
p-value(0)(0)(0)
Totaal_werklozen;Vanaf_25_jaar0.94070.94360.8062
p-value(0)(0)(0)
Totaal_werklozen;Belgie0.76350.76080.566
p-value(0)(0)(0)
Totaal_werklozen;Eurogebied0.43850.50490.3228
p-value(0)(0)(0)
Totaal_werklozen;EU_270.27670.39010.2584
p-value(8e-04)(0)(0)
Jonger_dan_25_jaar;Vanaf_25_jaar0.38050.40810.294
p-value(0)(0)(0)
Jonger_dan_25_jaar;Belgie0.48410.48360.353
p-value(0)(0)(0)
Jonger_dan_25_jaar;Eurogebied0.1690.19820.1337
p-value(0.0421)(0.0169)(0.02)
Jonger_dan_25_jaar;EU_270.25870.22530.1503
p-value(0.0017)(0.0064)(0.0092)
Vanaf_25_jaar;Belgie0.73250.72390.5402
p-value(0)(0)(0)
Vanaf_25_jaar;Eurogebied0.47040.51580.3447
p-value(0)(0)(0)
Vanaf_25_jaar;EU_270.22770.36260.2638
p-value(0.0059)(0)(0)
Belgie;Eurogebied0.41830.4750.335
p-value(0)(0)(0)
Belgie;EU_270.36460.41550.3059
p-value(0)(0)(0)
Eurogebied;EU_270.91510.94690.8515
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
Totaal_werklozen;Jonger_dan_25_jaar & 0.6714 & 0.6542 & 0.4938 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Totaal_werklozen;Vanaf_25_jaar & 0.9407 & 0.9436 & 0.8062 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Totaal_werklozen;Belgie & 0.7635 & 0.7608 & 0.566 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Totaal_werklozen;Eurogebied & 0.4385 & 0.5049 & 0.3228 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Totaal_werklozen;EU_27 & 0.2767 & 0.3901 & 0.2584 \tabularnewline
p-value & (8e-04) & (0) & (0) \tabularnewline
Jonger_dan_25_jaar;Vanaf_25_jaar & 0.3805 & 0.4081 & 0.294 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Jonger_dan_25_jaar;Belgie & 0.4841 & 0.4836 & 0.353 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Jonger_dan_25_jaar;Eurogebied & 0.169 & 0.1982 & 0.1337 \tabularnewline
p-value & (0.0421) & (0.0169) & (0.02) \tabularnewline
Jonger_dan_25_jaar;EU_27 & 0.2587 & 0.2253 & 0.1503 \tabularnewline
p-value & (0.0017) & (0.0064) & (0.0092) \tabularnewline
Vanaf_25_jaar;Belgie & 0.7325 & 0.7239 & 0.5402 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Vanaf_25_jaar;Eurogebied & 0.4704 & 0.5158 & 0.3447 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Vanaf_25_jaar;EU_27 & 0.2277 & 0.3626 & 0.2638 \tabularnewline
p-value & (0.0059) & (0) & (0) \tabularnewline
Belgie;Eurogebied & 0.4183 & 0.475 & 0.335 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Belgie;EU_27 & 0.3646 & 0.4155 & 0.3059 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Eurogebied;EU_27 & 0.9151 & 0.9469 & 0.8515 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=197474&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]Totaal_werklozen;Jonger_dan_25_jaar[/C][C]0.6714[/C][C]0.6542[/C][C]0.4938[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Totaal_werklozen;Vanaf_25_jaar[/C][C]0.9407[/C][C]0.9436[/C][C]0.8062[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Totaal_werklozen;Belgie[/C][C]0.7635[/C][C]0.7608[/C][C]0.566[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Totaal_werklozen;Eurogebied[/C][C]0.4385[/C][C]0.5049[/C][C]0.3228[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Totaal_werklozen;EU_27[/C][C]0.2767[/C][C]0.3901[/C][C]0.2584[/C][/ROW]
[ROW][C]p-value[/C][C](8e-04)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Jonger_dan_25_jaar;Vanaf_25_jaar[/C][C]0.3805[/C][C]0.4081[/C][C]0.294[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Jonger_dan_25_jaar;Belgie[/C][C]0.4841[/C][C]0.4836[/C][C]0.353[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Jonger_dan_25_jaar;Eurogebied[/C][C]0.169[/C][C]0.1982[/C][C]0.1337[/C][/ROW]
[ROW][C]p-value[/C][C](0.0421)[/C][C](0.0169)[/C][C](0.02)[/C][/ROW]
[ROW][C]Jonger_dan_25_jaar;EU_27[/C][C]0.2587[/C][C]0.2253[/C][C]0.1503[/C][/ROW]
[ROW][C]p-value[/C][C](0.0017)[/C][C](0.0064)[/C][C](0.0092)[/C][/ROW]
[ROW][C]Vanaf_25_jaar;Belgie[/C][C]0.7325[/C][C]0.7239[/C][C]0.5402[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Vanaf_25_jaar;Eurogebied[/C][C]0.4704[/C][C]0.5158[/C][C]0.3447[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Vanaf_25_jaar;EU_27[/C][C]0.2277[/C][C]0.3626[/C][C]0.2638[/C][/ROW]
[ROW][C]p-value[/C][C](0.0059)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Belgie;Eurogebied[/C][C]0.4183[/C][C]0.475[/C][C]0.335[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Belgie;EU_27[/C][C]0.3646[/C][C]0.4155[/C][C]0.3059[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Eurogebied;EU_27[/C][C]0.9151[/C][C]0.9469[/C][C]0.8515[/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=197474&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=197474&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
Totaal_werklozen;Jonger_dan_25_jaar0.67140.65420.4938
p-value(0)(0)(0)
Totaal_werklozen;Vanaf_25_jaar0.94070.94360.8062
p-value(0)(0)(0)
Totaal_werklozen;Belgie0.76350.76080.566
p-value(0)(0)(0)
Totaal_werklozen;Eurogebied0.43850.50490.3228
p-value(0)(0)(0)
Totaal_werklozen;EU_270.27670.39010.2584
p-value(8e-04)(0)(0)
Jonger_dan_25_jaar;Vanaf_25_jaar0.38050.40810.294
p-value(0)(0)(0)
Jonger_dan_25_jaar;Belgie0.48410.48360.353
p-value(0)(0)(0)
Jonger_dan_25_jaar;Eurogebied0.1690.19820.1337
p-value(0.0421)(0.0169)(0.02)
Jonger_dan_25_jaar;EU_270.25870.22530.1503
p-value(0.0017)(0.0064)(0.0092)
Vanaf_25_jaar;Belgie0.73250.72390.5402
p-value(0)(0)(0)
Vanaf_25_jaar;Eurogebied0.47040.51580.3447
p-value(0)(0)(0)
Vanaf_25_jaar;EU_270.22770.36260.2638
p-value(0.0059)(0)(0)
Belgie;Eurogebied0.41830.4750.335
p-value(0)(0)(0)
Belgie;EU_270.36460.41550.3059
p-value(0)(0)(0)
Eurogebied;EU_270.91510.94690.8515
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')