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Author*The author of this computation has been verified*
R Software ModulePatrick.Wessarwasp_pairs.wasp
Title produced by softwareKendall tau Correlation Matrix
Date of computationTue, 14 Dec 2010 14:45:10 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/14/t12923378028asof58xsccgwj1.htm/, Retrieved Thu, 02 May 2024 20:57:09 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=109701, Retrieved Thu, 02 May 2024 20:57:09 +0000
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Estimated Impact149
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 17:44:33] [b98453cac15ba1066b407e146608df68]
-   PD  [Kendall tau Correlation Matrix] [WS10: pearson cor...] [2010-12-14 14:34:58] [d672a41e0af7ff107c03f1d65e47fd32]
-   P       [Kendall tau Correlation Matrix] [WS10: kendall's t...] [2010-12-14 14:45:10] [4c7d8c32b2e34fcaa7f14928b91d45ae] [Current]
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Dataseries X:
1.0800	1.0100	1.6100	1.7700	1.3900	1.7700
1.0900	1.0000	1.5800	1.7700	1.3500	1.9800
1.1000	1.0000	1.6900	1.7700	1.3900	1.9400
1.1000	1.0000	1.7800	1.7700	1.3700	1.8500
1.1100	1.0600	1.7600	1.7400	1.3800	1.8400
1.1000	1.2200	1.8300	1.7800	1.5100	1.8200
1.1000	1.2400	1.8000	1.7800	1.5100	1.8300
1.1100	1.3400	1.5700	1.7800	1.4500	1.9100
1.1100	1.3000	1.4500	1.7800	1.3000	1.8500
1.1100	1.0500	1.4000	1.8100	1.2900	1.8100
1.1100	1.0000	1.5500	1.8400	1.4400	1.8300
1.1100	1.0000	1.5800	1.8000	1.4600	1.7900
1.1200	1.0100	1.5800	1.7800	1.5000	1.8000
1.1100	1.0200	1.5900	1.7600	1.3900	1.8200
1.1100	1.0600	1.8000	1.7400	1.4800	1.8800
1.1200	1.0900	1.9900	1.7200	1.5200	2.0100
1.1200	1.0900	2.0600	1.7300	1.6800	1.9700
1.1100	1.1500	2.0600	1.7700	1.7400	1.9200
1.1200	1.2500	2.0800	1.8100	1.7200	1.9800
1.1100	1.3700	2.0000	1.8300	1.7400	2.0200
1.1100	1.5100	1.8500	1.8700	1.8300	1.9000
1.1000	1.3500	1.7700	1.8900	1.9900	1.9400
1.1000	1.3200	1.7000	1.8200	1.8500	1.9600
1.1000	1.3000	1.6600	1.7900	1.6800	1.8400
1.1100	1.3900	1.6700	1.7900	1.6200	1.8700
1.1000	1.4000	1.7300	1.8200	1.6200	1.8400
1.1000	1.3900	1.9100	1.8200	1.6400	2.0700
1.0900	1.4200	2.0200	1.8100	1.5900	2.0800
1.1000	1.4400	2.0700	1.8100	1.6300	2.1400
1.1000	1.4400	2.1500	1.7800	1.6800	2.1500
1.1100	1.4500	2.1000	1.8000	1.5900	2.0500
1.1300	1.3900	1.6800	1.7900	1.5400	2.0500
1.1300	1.4800	1.6800	1.8300	1.5100	1.9500
1.1300	1.3200	1.6500	1.8200	1.5000	2.0200
1.1300	1.2900	1.7200	1.8000	1.7100	2.0200
1.1400	1.3100	1.7300	1.8200	1.6000	1.8800
1.1400	1.2700	1.7600	1.8400	1.5500	1.9600
1.1400	1.3800	1.8400	1.8200	1.6300	1.9300
1.1500	1.3800	1.9900	1.8100	1.6400	2.0300
1.1500	1.4500	2.0500	1.7900	1.6800	2.1000
1.1500	1.5000	2.1200	1.8700	1.7200	1.9500
1.1500	1.6300	2.1300	1.8900	1.7600	2.0700
1.1500	1.7300	2.0800	1.9200	1.8400	2.0900
1.1500	1.8400	1.8800	1.9000	1.8900	2.0100
1.1400	1.7500	1.8100	1.9100	1.8600	1.9200
1.1400	1.3400	1.8100	1.9500	1.8100	1.9900
1.1400	1.3600	1.8800	2.0400	1.8300	2.1100
1.1300	1.3300	1.8700	1.9900	1.7200	2.0000
1.1200	1.3700	1.8700	1.9400	1.5900	2.0900
1.1300	1.3900	1.9000	1.9300	1.6600	2.0400
1.1300	1.4000	2.0100	1.8900	1.5900	2.0900
1.1300	1.4000	2.0500	1.8700	1.6000	2.0900
1.1200	1.4300	2.1600	1.8900	1.5600	2.1300
1.1300	1.5200	2.1800	1.9000	1.6000	2.1300
1.1200	1.5400	2.1500	1.9300	1.6200	2.1700
1.1200	1.8500	2.1200	1.9400	1.6000	2.1300
1.1100	1.8300	2.0400	1.8800	1.6000	2.0000
1.1100	1.2900	2.0400	1.8900	1.6800	2.0500
1.1100	1.2000	2.0600	1.9200	1.7700	2.0800
1.1100	1.2000	1.9300	1.9100	1.7500	2.0700
1.1400	1.2100	1.8600	1.8900	1.7600	2.1200
1.1500	1.2100	1.9400	1.8900	1.8900	2.1300
1.1500	1.1900	2.3500	1.9800	1.8800	2.1600
1.1600	1.1800	2.4600	2.0200	1.9000	2.2500
1.1500	1.1700	2.5900	2.0200	1.9100	2.2600
1.1600	1.2200	2.6600	1.9900	1.9100	2.3900
1.1300	1.2500	2.4100	1.9700	1.8400	2.3600
1.1300	1.3000	2.1800	1.9600	1.6900	2.2600
1.1200	1.3300	2.1300	1.9500	1.6100	2.2600
1.1200	1.1800	2.1100	1.9800	1.6700	2.2700
1.1100	1.1800	2.1200	2.0000	1.8400	2.2900
1.1100	1.1900	2.1600	2.0000	1.8400	2.2100




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109701&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=109701&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109701&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'Gwilym Jenkins' @ 72.249.127.135







Correlations for all pairs of data series (method=kendall)
VruchtesappenJonagoldSinaasappelenCitroenenPompelmoezenBananen
Vruchtesappen10.1870.2830.3770.3480.303
Jonagold0.18710.2040.170.1480.191
Sinaasappelen0.2830.20410.420.420.632
Citroenen0.3770.170.4210.4840.51
Pompelmoezen0.3480.1480.420.48410.386
Bananen0.3030.1910.6320.510.3861

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=kendall) \tabularnewline
  & Vruchtesappen & Jonagold & Sinaasappelen & Citroenen & Pompelmoezen & Bananen \tabularnewline
Vruchtesappen & 1 & 0.187 & 0.283 & 0.377 & 0.348 & 0.303 \tabularnewline
Jonagold & 0.187 & 1 & 0.204 & 0.17 & 0.148 & 0.191 \tabularnewline
Sinaasappelen & 0.283 & 0.204 & 1 & 0.42 & 0.42 & 0.632 \tabularnewline
Citroenen & 0.377 & 0.17 & 0.42 & 1 & 0.484 & 0.51 \tabularnewline
Pompelmoezen & 0.348 & 0.148 & 0.42 & 0.484 & 1 & 0.386 \tabularnewline
Bananen & 0.303 & 0.191 & 0.632 & 0.51 & 0.386 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109701&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=kendall)[/C][/ROW]
[ROW][C] [/C][C]Vruchtesappen[/C][C]Jonagold[/C][C]Sinaasappelen[/C][C]Citroenen[/C][C]Pompelmoezen[/C][C]Bananen[/C][/ROW]
[ROW][C]Vruchtesappen[/C][C]1[/C][C]0.187[/C][C]0.283[/C][C]0.377[/C][C]0.348[/C][C]0.303[/C][/ROW]
[ROW][C]Jonagold[/C][C]0.187[/C][C]1[/C][C]0.204[/C][C]0.17[/C][C]0.148[/C][C]0.191[/C][/ROW]
[ROW][C]Sinaasappelen[/C][C]0.283[/C][C]0.204[/C][C]1[/C][C]0.42[/C][C]0.42[/C][C]0.632[/C][/ROW]
[ROW][C]Citroenen[/C][C]0.377[/C][C]0.17[/C][C]0.42[/C][C]1[/C][C]0.484[/C][C]0.51[/C][/ROW]
[ROW][C]Pompelmoezen[/C][C]0.348[/C][C]0.148[/C][C]0.42[/C][C]0.484[/C][C]1[/C][C]0.386[/C][/ROW]
[ROW][C]Bananen[/C][C]0.303[/C][C]0.191[/C][C]0.632[/C][C]0.51[/C][C]0.386[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=109701&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109701&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)
VruchtesappenJonagoldSinaasappelenCitroenenPompelmoezenBananen
Vruchtesappen10.1870.2830.3770.3480.303
Jonagold0.18710.2040.170.1480.191
Sinaasappelen0.2830.20410.420.420.632
Citroenen0.3770.170.4210.4840.51
Pompelmoezen0.3480.1480.420.48410.386
Bananen0.3030.1910.6320.510.3861







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
Vruchtesappen;Jonagold0.30880.25710.1866
p-value(0.0083)(0.0293)(0.031)
Vruchtesappen;Sinaasappelen0.44820.37740.2832
p-value(1e-04)(0.0011)(0.001)
Vruchtesappen;Citroenen0.49770.51680.3769
p-value(0)(0)(0)
Vruchtesappen;Pompelmoezen0.4950.44570.3478
p-value(0)(1e-04)(1e-04)
Vruchtesappen;Bananen0.43450.42110.3029
p-value(1e-04)(2e-04)(5e-04)
Jonagold;Sinaasappelen0.24030.28440.2045
p-value(0.042)(0.0155)(0.012)
Jonagold;Citroenen0.27780.27770.1705
p-value(0.0181)(0.0182)(0.0388)
Jonagold;Pompelmoezen0.35690.24150.1478
p-value(0.0021)(0.041)(0.0709)
Jonagold;Bananen0.22660.26780.1912
p-value(0.0556)(0.0229)(0.0192)
Sinaasappelen;Citroenen0.60690.5790.4195
p-value(0)(0)(0)
Sinaasappelen;Pompelmoezen0.62360.57460.4202
p-value(0)(0)(0)
Sinaasappelen;Bananen0.82960.82290.6318
p-value(0)(0)(0)
Citroenen;Pompelmoezen0.66290.65670.4839
p-value(0)(0)(0)
Citroenen;Bananen0.72370.69220.5096
p-value(0)(0)(0)
Pompelmoezen;Bananen0.57150.53470.386
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
Vruchtesappen;Jonagold & 0.3088 & 0.2571 & 0.1866 \tabularnewline
p-value & (0.0083) & (0.0293) & (0.031) \tabularnewline
Vruchtesappen;Sinaasappelen & 0.4482 & 0.3774 & 0.2832 \tabularnewline
p-value & (1e-04) & (0.0011) & (0.001) \tabularnewline
Vruchtesappen;Citroenen & 0.4977 & 0.5168 & 0.3769 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Vruchtesappen;Pompelmoezen & 0.495 & 0.4457 & 0.3478 \tabularnewline
p-value & (0) & (1e-04) & (1e-04) \tabularnewline
Vruchtesappen;Bananen & 0.4345 & 0.4211 & 0.3029 \tabularnewline
p-value & (1e-04) & (2e-04) & (5e-04) \tabularnewline
Jonagold;Sinaasappelen & 0.2403 & 0.2844 & 0.2045 \tabularnewline
p-value & (0.042) & (0.0155) & (0.012) \tabularnewline
Jonagold;Citroenen & 0.2778 & 0.2777 & 0.1705 \tabularnewline
p-value & (0.0181) & (0.0182) & (0.0388) \tabularnewline
Jonagold;Pompelmoezen & 0.3569 & 0.2415 & 0.1478 \tabularnewline
p-value & (0.0021) & (0.041) & (0.0709) \tabularnewline
Jonagold;Bananen & 0.2266 & 0.2678 & 0.1912 \tabularnewline
p-value & (0.0556) & (0.0229) & (0.0192) \tabularnewline
Sinaasappelen;Citroenen & 0.6069 & 0.579 & 0.4195 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Sinaasappelen;Pompelmoezen & 0.6236 & 0.5746 & 0.4202 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Sinaasappelen;Bananen & 0.8296 & 0.8229 & 0.6318 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Citroenen;Pompelmoezen & 0.6629 & 0.6567 & 0.4839 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Citroenen;Bananen & 0.7237 & 0.6922 & 0.5096 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Pompelmoezen;Bananen & 0.5715 & 0.5347 & 0.386 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109701&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]Vruchtesappen;Jonagold[/C][C]0.3088[/C][C]0.2571[/C][C]0.1866[/C][/ROW]
[ROW][C]p-value[/C][C](0.0083)[/C][C](0.0293)[/C][C](0.031)[/C][/ROW]
[ROW][C]Vruchtesappen;Sinaasappelen[/C][C]0.4482[/C][C]0.3774[/C][C]0.2832[/C][/ROW]
[ROW][C]p-value[/C][C](1e-04)[/C][C](0.0011)[/C][C](0.001)[/C][/ROW]
[ROW][C]Vruchtesappen;Citroenen[/C][C]0.4977[/C][C]0.5168[/C][C]0.3769[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Vruchtesappen;Pompelmoezen[/C][C]0.495[/C][C]0.4457[/C][C]0.3478[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](1e-04)[/C][C](1e-04)[/C][/ROW]
[ROW][C]Vruchtesappen;Bananen[/C][C]0.4345[/C][C]0.4211[/C][C]0.3029[/C][/ROW]
[ROW][C]p-value[/C][C](1e-04)[/C][C](2e-04)[/C][C](5e-04)[/C][/ROW]
[ROW][C]Jonagold;Sinaasappelen[/C][C]0.2403[/C][C]0.2844[/C][C]0.2045[/C][/ROW]
[ROW][C]p-value[/C][C](0.042)[/C][C](0.0155)[/C][C](0.012)[/C][/ROW]
[ROW][C]Jonagold;Citroenen[/C][C]0.2778[/C][C]0.2777[/C][C]0.1705[/C][/ROW]
[ROW][C]p-value[/C][C](0.0181)[/C][C](0.0182)[/C][C](0.0388)[/C][/ROW]
[ROW][C]Jonagold;Pompelmoezen[/C][C]0.3569[/C][C]0.2415[/C][C]0.1478[/C][/ROW]
[ROW][C]p-value[/C][C](0.0021)[/C][C](0.041)[/C][C](0.0709)[/C][/ROW]
[ROW][C]Jonagold;Bananen[/C][C]0.2266[/C][C]0.2678[/C][C]0.1912[/C][/ROW]
[ROW][C]p-value[/C][C](0.0556)[/C][C](0.0229)[/C][C](0.0192)[/C][/ROW]
[ROW][C]Sinaasappelen;Citroenen[/C][C]0.6069[/C][C]0.579[/C][C]0.4195[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Sinaasappelen;Pompelmoezen[/C][C]0.6236[/C][C]0.5746[/C][C]0.4202[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Sinaasappelen;Bananen[/C][C]0.8296[/C][C]0.8229[/C][C]0.6318[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Citroenen;Pompelmoezen[/C][C]0.6629[/C][C]0.6567[/C][C]0.4839[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Citroenen;Bananen[/C][C]0.7237[/C][C]0.6922[/C][C]0.5096[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Pompelmoezen;Bananen[/C][C]0.5715[/C][C]0.5347[/C][C]0.386[/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=109701&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109701&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
Vruchtesappen;Jonagold0.30880.25710.1866
p-value(0.0083)(0.0293)(0.031)
Vruchtesappen;Sinaasappelen0.44820.37740.2832
p-value(1e-04)(0.0011)(0.001)
Vruchtesappen;Citroenen0.49770.51680.3769
p-value(0)(0)(0)
Vruchtesappen;Pompelmoezen0.4950.44570.3478
p-value(0)(1e-04)(1e-04)
Vruchtesappen;Bananen0.43450.42110.3029
p-value(1e-04)(2e-04)(5e-04)
Jonagold;Sinaasappelen0.24030.28440.2045
p-value(0.042)(0.0155)(0.012)
Jonagold;Citroenen0.27780.27770.1705
p-value(0.0181)(0.0182)(0.0388)
Jonagold;Pompelmoezen0.35690.24150.1478
p-value(0.0021)(0.041)(0.0709)
Jonagold;Bananen0.22660.26780.1912
p-value(0.0556)(0.0229)(0.0192)
Sinaasappelen;Citroenen0.60690.5790.4195
p-value(0)(0)(0)
Sinaasappelen;Pompelmoezen0.62360.57460.4202
p-value(0)(0)(0)
Sinaasappelen;Bananen0.82960.82290.6318
p-value(0)(0)(0)
Citroenen;Pompelmoezen0.66290.65670.4839
p-value(0)(0)(0)
Citroenen;Bananen0.72370.69220.5096
p-value(0)(0)(0)
Pompelmoezen;Bananen0.57150.53470.386
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')