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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 computationMon, 13 Dec 2010 19:10:16 +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/13/t1292267278iyev9ieta9oi9qu.htm/, Retrieved Mon, 06 May 2024 19:02:07 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=109082, Retrieved Mon, 06 May 2024 19:02:07 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact133
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]
-   PD    [Kendall tau Correlation Matrix] [] [2010-12-13 19:10:16] [f9aa24c2294a5d3925c7278aa2e9a372] [Current]
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Dataseries X:
1	15	15	11	12	13	6
0	9	12	12	7	11	4
0	12	15	12	13	14	6
0	15	12	11	11	12	5
0	17	14	11	16	12	5
0	14	8	10	10	6	4
1	9	11	11	15	10	5
1	12	15	9	5	11	3
0	11	4	10	4	10	2
0	13	13	12	7	12	5
1	16	19	12	15	15	6
1	16	10	12	5	13	6
0	10	6	9	15	11	6
1	16	7	12	13	12	3
0	12	14	12	13	13	6
0	15	16	12	15	14	6
1	13	16	12	15	16	7
1	18	14	13	10	16	8
0	13	15	11	17	16	6
1	17	14	12	14	15	7
1	14	12	12	9	13	4
0	13	9	15	6	8	4
1	13	12	11	11	14	2
1	15	14	12	13	15	6
1	13	12	10	12	13	6
1	15	14	11	10	16	6
1	13	10	13	4	13	6
1	14	14	6	13	12	6
1	13	16	12	15	15	7
1	14	8	10	10	14	3
1	15	11	12	7	13	6
0	9	8	11	9	12	4
0	16	13	9	14	14	6
1	16	11	10	5	13	3
0	13	16	12	16	14	6
1	17	16	11	14	15	6
1	15	13	12	16	16	6
1	14	14	11	15	15	8
0	10	5	14	4	5	2
0	13	14	10	12	15	6
0	16	14	11	15	16	6
0	16	14	11	15	16	6
1	15	11	10	12	14	5
1	15	15	12	13	13	6
1	12	16	11	14	14	6
0	15	11	12	15	12	6
1	17	10	11	13	15	6
1	10	8	7	4	13	6
0	11	9	11	8	10	4
1	15	12	8	13	13	5
0	15	14	11	15	14	6
1	7	12	12	15	13	6
0	14	14	14	17	18	6
1	12	16	12	14	16	8
1	14	13	13	11	15	6
1	11	11	8	10	14	5
1	16	15	12	14	16	4
1	16	6	12	6	11	2
0	11	12	11	16	13	4
0	15	13	13	15	14	6
0	14	8	12	8	14	5
1	15	9	11	9	12	4
1	17	10	12	8	16	4
1	19	16	12	14	14	6
0	16	14	11	14	12	6
1	14	12	8	15	13	7
1	15	12	12	12	13	4
0	17	8	13	7	10	3
1	12	16	12	12	15	8
1	13	12	12	10	13	4
1	14	12	10	14	14	5
1	14	8	7	9	15	4
0	12	13	12	14	14	6
1	13	12	13	14	12	5
1	17	12	12	15	13	6
1	16	12	12	6	14	5
1	15	4	8	6	4	4




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109082&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=109082&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109082&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'George Udny Yule' @ 72.249.76.132







Correlations for all pairs of data series (method=pearson)
GenderPerceived_happinessPopularityFinding_friendsKnowing_peopleLikedCelebrity
Gender10.2030.099-0.179-0.0960.2240.098
Perceived_happiness0.20310.2030.1110.1220.2750.116
Popularity0.0990.20310.180.6110.6430.636
Finding_friends-0.1790.1110.1810.0450.0980.049
Knowing_people-0.0960.1220.6110.04510.4910.549
Liked0.2240.2750.6430.0980.49110.542
Celebrity0.0980.1160.6360.0490.5490.5421

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & Gender & Perceived_happiness & Popularity & Finding_friends & Knowing_people & Liked & Celebrity \tabularnewline
Gender & 1 & 0.203 & 0.099 & -0.179 & -0.096 & 0.224 & 0.098 \tabularnewline
Perceived_happiness & 0.203 & 1 & 0.203 & 0.111 & 0.122 & 0.275 & 0.116 \tabularnewline
Popularity & 0.099 & 0.203 & 1 & 0.18 & 0.611 & 0.643 & 0.636 \tabularnewline
Finding_friends & -0.179 & 0.111 & 0.18 & 1 & 0.045 & 0.098 & 0.049 \tabularnewline
Knowing_people & -0.096 & 0.122 & 0.611 & 0.045 & 1 & 0.491 & 0.549 \tabularnewline
Liked & 0.224 & 0.275 & 0.643 & 0.098 & 0.491 & 1 & 0.542 \tabularnewline
Celebrity & 0.098 & 0.116 & 0.636 & 0.049 & 0.549 & 0.542 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109082&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]Gender[/C][C]Perceived_happiness[/C][C]Popularity[/C][C]Finding_friends[/C][C]Knowing_people[/C][C]Liked[/C][C]Celebrity[/C][/ROW]
[ROW][C]Gender[/C][C]1[/C][C]0.203[/C][C]0.099[/C][C]-0.179[/C][C]-0.096[/C][C]0.224[/C][C]0.098[/C][/ROW]
[ROW][C]Perceived_happiness[/C][C]0.203[/C][C]1[/C][C]0.203[/C][C]0.111[/C][C]0.122[/C][C]0.275[/C][C]0.116[/C][/ROW]
[ROW][C]Popularity[/C][C]0.099[/C][C]0.203[/C][C]1[/C][C]0.18[/C][C]0.611[/C][C]0.643[/C][C]0.636[/C][/ROW]
[ROW][C]Finding_friends[/C][C]-0.179[/C][C]0.111[/C][C]0.18[/C][C]1[/C][C]0.045[/C][C]0.098[/C][C]0.049[/C][/ROW]
[ROW][C]Knowing_people[/C][C]-0.096[/C][C]0.122[/C][C]0.611[/C][C]0.045[/C][C]1[/C][C]0.491[/C][C]0.549[/C][/ROW]
[ROW][C]Liked[/C][C]0.224[/C][C]0.275[/C][C]0.643[/C][C]0.098[/C][C]0.491[/C][C]1[/C][C]0.542[/C][/ROW]
[ROW][C]Celebrity[/C][C]0.098[/C][C]0.116[/C][C]0.636[/C][C]0.049[/C][C]0.549[/C][C]0.542[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=109082&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109082&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)
GenderPerceived_happinessPopularityFinding_friendsKnowing_peopleLikedCelebrity
Gender10.2030.099-0.179-0.0960.2240.098
Perceived_happiness0.20310.2030.1110.1220.2750.116
Popularity0.0990.20310.180.6110.6430.636
Finding_friends-0.1790.1110.1810.0450.0980.049
Knowing_people-0.0960.1220.6110.04510.4910.549
Liked0.2240.2750.6430.0980.49110.542
Celebrity0.0980.1160.6360.0490.5490.5421







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
Gender;Perceived_happiness0.20280.20160.1748
p-value(0.077)(0.0787)(0.0788)
Gender;Popularity0.09920.0480.0414
p-value(0.3906)(0.6782)(0.6753)
Gender;Finding_friends-0.1786-0.0736-0.0663
p-value(0.1201)(0.5245)(0.521)
Gender;Knowing_people-0.096-0.153-0.1308
p-value(0.4063)(0.1842)(0.1824)
Gender;Liked0.22390.22250.1946
p-value(0.0503)(0.0518)(0.0524)
Gender;Celebrity0.09830.09170.0831
p-value(0.3952)(0.4277)(0.4241)
Perceived_happiness;Popularity0.20270.11950.0832
p-value(0.077)(0.3007)(0.3322)
Perceived_happiness;Finding_friends0.11070.11280.0938
p-value(0.3378)(0.3287)(0.2958)
Perceived_happiness;Knowing_people0.12230.09230.0721
p-value(0.2892)(0.4247)(0.3972)
Perceived_happiness;Liked0.27480.26180.1949
p-value(0.0156)(0.0214)(0.0252)
Perceived_happiness;Celebrity0.11570.08460.0649
p-value(0.3161)(0.4642)(0.4718)
Popularity;Finding_friends0.17990.16430.1319
p-value(0.1175)(0.1534)(0.1388)
Popularity;Knowing_people0.61060.56930.4352
p-value(0)(0)(0)
Popularity;Liked0.64270.57640.4566
p-value(0)(0)(0)
Popularity;Celebrity0.63580.63080.5307
p-value(0)(0)(0)
Finding_friends;Knowing_people0.04460.02880.0197
p-value(0.6998)(0.8039)(0.8241)
Finding_friends;Liked0.09790.12540.1029
p-value(0.3968)(0.2773)(0.2551)
Finding_friends;Celebrity0.0490.1260.1056
p-value(0.672)(0.2749)(0.2596)
Knowing_people;Liked0.49050.41950.3221
p-value(0)(1e-04)(2e-04)
Knowing_people;Celebrity0.54850.54060.4306
p-value(0)(0)(0)
Liked;Celebrity0.54240.55050.457
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
Gender;Perceived_happiness & 0.2028 & 0.2016 & 0.1748 \tabularnewline
p-value & (0.077) & (0.0787) & (0.0788) \tabularnewline
Gender;Popularity & 0.0992 & 0.048 & 0.0414 \tabularnewline
p-value & (0.3906) & (0.6782) & (0.6753) \tabularnewline
Gender;Finding_friends & -0.1786 & -0.0736 & -0.0663 \tabularnewline
p-value & (0.1201) & (0.5245) & (0.521) \tabularnewline
Gender;Knowing_people & -0.096 & -0.153 & -0.1308 \tabularnewline
p-value & (0.4063) & (0.1842) & (0.1824) \tabularnewline
Gender;Liked & 0.2239 & 0.2225 & 0.1946 \tabularnewline
p-value & (0.0503) & (0.0518) & (0.0524) \tabularnewline
Gender;Celebrity & 0.0983 & 0.0917 & 0.0831 \tabularnewline
p-value & (0.3952) & (0.4277) & (0.4241) \tabularnewline
Perceived_happiness;Popularity & 0.2027 & 0.1195 & 0.0832 \tabularnewline
p-value & (0.077) & (0.3007) & (0.3322) \tabularnewline
Perceived_happiness;Finding_friends & 0.1107 & 0.1128 & 0.0938 \tabularnewline
p-value & (0.3378) & (0.3287) & (0.2958) \tabularnewline
Perceived_happiness;Knowing_people & 0.1223 & 0.0923 & 0.0721 \tabularnewline
p-value & (0.2892) & (0.4247) & (0.3972) \tabularnewline
Perceived_happiness;Liked & 0.2748 & 0.2618 & 0.1949 \tabularnewline
p-value & (0.0156) & (0.0214) & (0.0252) \tabularnewline
Perceived_happiness;Celebrity & 0.1157 & 0.0846 & 0.0649 \tabularnewline
p-value & (0.3161) & (0.4642) & (0.4718) \tabularnewline
Popularity;Finding_friends & 0.1799 & 0.1643 & 0.1319 \tabularnewline
p-value & (0.1175) & (0.1534) & (0.1388) \tabularnewline
Popularity;Knowing_people & 0.6106 & 0.5693 & 0.4352 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Popularity;Liked & 0.6427 & 0.5764 & 0.4566 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Popularity;Celebrity & 0.6358 & 0.6308 & 0.5307 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Finding_friends;Knowing_people & 0.0446 & 0.0288 & 0.0197 \tabularnewline
p-value & (0.6998) & (0.8039) & (0.8241) \tabularnewline
Finding_friends;Liked & 0.0979 & 0.1254 & 0.1029 \tabularnewline
p-value & (0.3968) & (0.2773) & (0.2551) \tabularnewline
Finding_friends;Celebrity & 0.049 & 0.126 & 0.1056 \tabularnewline
p-value & (0.672) & (0.2749) & (0.2596) \tabularnewline
Knowing_people;Liked & 0.4905 & 0.4195 & 0.3221 \tabularnewline
p-value & (0) & (1e-04) & (2e-04) \tabularnewline
Knowing_people;Celebrity & 0.5485 & 0.5406 & 0.4306 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Liked;Celebrity & 0.5424 & 0.5505 & 0.457 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=109082&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]Gender;Perceived_happiness[/C][C]0.2028[/C][C]0.2016[/C][C]0.1748[/C][/ROW]
[ROW][C]p-value[/C][C](0.077)[/C][C](0.0787)[/C][C](0.0788)[/C][/ROW]
[ROW][C]Gender;Popularity[/C][C]0.0992[/C][C]0.048[/C][C]0.0414[/C][/ROW]
[ROW][C]p-value[/C][C](0.3906)[/C][C](0.6782)[/C][C](0.6753)[/C][/ROW]
[ROW][C]Gender;Finding_friends[/C][C]-0.1786[/C][C]-0.0736[/C][C]-0.0663[/C][/ROW]
[ROW][C]p-value[/C][C](0.1201)[/C][C](0.5245)[/C][C](0.521)[/C][/ROW]
[ROW][C]Gender;Knowing_people[/C][C]-0.096[/C][C]-0.153[/C][C]-0.1308[/C][/ROW]
[ROW][C]p-value[/C][C](0.4063)[/C][C](0.1842)[/C][C](0.1824)[/C][/ROW]
[ROW][C]Gender;Liked[/C][C]0.2239[/C][C]0.2225[/C][C]0.1946[/C][/ROW]
[ROW][C]p-value[/C][C](0.0503)[/C][C](0.0518)[/C][C](0.0524)[/C][/ROW]
[ROW][C]Gender;Celebrity[/C][C]0.0983[/C][C]0.0917[/C][C]0.0831[/C][/ROW]
[ROW][C]p-value[/C][C](0.3952)[/C][C](0.4277)[/C][C](0.4241)[/C][/ROW]
[ROW][C]Perceived_happiness;Popularity[/C][C]0.2027[/C][C]0.1195[/C][C]0.0832[/C][/ROW]
[ROW][C]p-value[/C][C](0.077)[/C][C](0.3007)[/C][C](0.3322)[/C][/ROW]
[ROW][C]Perceived_happiness;Finding_friends[/C][C]0.1107[/C][C]0.1128[/C][C]0.0938[/C][/ROW]
[ROW][C]p-value[/C][C](0.3378)[/C][C](0.3287)[/C][C](0.2958)[/C][/ROW]
[ROW][C]Perceived_happiness;Knowing_people[/C][C]0.1223[/C][C]0.0923[/C][C]0.0721[/C][/ROW]
[ROW][C]p-value[/C][C](0.2892)[/C][C](0.4247)[/C][C](0.3972)[/C][/ROW]
[ROW][C]Perceived_happiness;Liked[/C][C]0.2748[/C][C]0.2618[/C][C]0.1949[/C][/ROW]
[ROW][C]p-value[/C][C](0.0156)[/C][C](0.0214)[/C][C](0.0252)[/C][/ROW]
[ROW][C]Perceived_happiness;Celebrity[/C][C]0.1157[/C][C]0.0846[/C][C]0.0649[/C][/ROW]
[ROW][C]p-value[/C][C](0.3161)[/C][C](0.4642)[/C][C](0.4718)[/C][/ROW]
[ROW][C]Popularity;Finding_friends[/C][C]0.1799[/C][C]0.1643[/C][C]0.1319[/C][/ROW]
[ROW][C]p-value[/C][C](0.1175)[/C][C](0.1534)[/C][C](0.1388)[/C][/ROW]
[ROW][C]Popularity;Knowing_people[/C][C]0.6106[/C][C]0.5693[/C][C]0.4352[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Popularity;Liked[/C][C]0.6427[/C][C]0.5764[/C][C]0.4566[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Popularity;Celebrity[/C][C]0.6358[/C][C]0.6308[/C][C]0.5307[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Finding_friends;Knowing_people[/C][C]0.0446[/C][C]0.0288[/C][C]0.0197[/C][/ROW]
[ROW][C]p-value[/C][C](0.6998)[/C][C](0.8039)[/C][C](0.8241)[/C][/ROW]
[ROW][C]Finding_friends;Liked[/C][C]0.0979[/C][C]0.1254[/C][C]0.1029[/C][/ROW]
[ROW][C]p-value[/C][C](0.3968)[/C][C](0.2773)[/C][C](0.2551)[/C][/ROW]
[ROW][C]Finding_friends;Celebrity[/C][C]0.049[/C][C]0.126[/C][C]0.1056[/C][/ROW]
[ROW][C]p-value[/C][C](0.672)[/C][C](0.2749)[/C][C](0.2596)[/C][/ROW]
[ROW][C]Knowing_people;Liked[/C][C]0.4905[/C][C]0.4195[/C][C]0.3221[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](1e-04)[/C][C](2e-04)[/C][/ROW]
[ROW][C]Knowing_people;Celebrity[/C][C]0.5485[/C][C]0.5406[/C][C]0.4306[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Liked;Celebrity[/C][C]0.5424[/C][C]0.5505[/C][C]0.457[/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=109082&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=109082&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
Gender;Perceived_happiness0.20280.20160.1748
p-value(0.077)(0.0787)(0.0788)
Gender;Popularity0.09920.0480.0414
p-value(0.3906)(0.6782)(0.6753)
Gender;Finding_friends-0.1786-0.0736-0.0663
p-value(0.1201)(0.5245)(0.521)
Gender;Knowing_people-0.096-0.153-0.1308
p-value(0.4063)(0.1842)(0.1824)
Gender;Liked0.22390.22250.1946
p-value(0.0503)(0.0518)(0.0524)
Gender;Celebrity0.09830.09170.0831
p-value(0.3952)(0.4277)(0.4241)
Perceived_happiness;Popularity0.20270.11950.0832
p-value(0.077)(0.3007)(0.3322)
Perceived_happiness;Finding_friends0.11070.11280.0938
p-value(0.3378)(0.3287)(0.2958)
Perceived_happiness;Knowing_people0.12230.09230.0721
p-value(0.2892)(0.4247)(0.3972)
Perceived_happiness;Liked0.27480.26180.1949
p-value(0.0156)(0.0214)(0.0252)
Perceived_happiness;Celebrity0.11570.08460.0649
p-value(0.3161)(0.4642)(0.4718)
Popularity;Finding_friends0.17990.16430.1319
p-value(0.1175)(0.1534)(0.1388)
Popularity;Knowing_people0.61060.56930.4352
p-value(0)(0)(0)
Popularity;Liked0.64270.57640.4566
p-value(0)(0)(0)
Popularity;Celebrity0.63580.63080.5307
p-value(0)(0)(0)
Finding_friends;Knowing_people0.04460.02880.0197
p-value(0.6998)(0.8039)(0.8241)
Finding_friends;Liked0.09790.12540.1029
p-value(0.3968)(0.2773)(0.2551)
Finding_friends;Celebrity0.0490.1260.1056
p-value(0.672)(0.2749)(0.2596)
Knowing_people;Liked0.49050.41950.3221
p-value(0)(1e-04)(2e-04)
Knowing_people;Celebrity0.54850.54060.4306
p-value(0)(0)(0)
Liked;Celebrity0.54240.55050.457
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')