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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 computationWed, 22 Dec 2010 08:54:08 +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/22/t1293007938519hhrhl57hbbym.htm/, Retrieved Sun, 05 May 2024 23:04:43 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=114115, Retrieved Sun, 05 May 2024 23:04:43 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact135
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]
- R PD  [Kendall tau Correlation Matrix] [Workshop 10; Pear...] [2010-12-13 21:11:58] [8ffb4cfa64b4677df0d2c448735a40bb]
-    D    [Kendall tau Correlation Matrix] [Workshop 10; Pear...] [2010-12-14 08:55:42] [8ffb4cfa64b4677df0d2c448735a40bb]
-    D      [Kendall tau Correlation Matrix] [Paper; Pearson Co...] [2010-12-22 08:34:36] [8ffb4cfa64b4677df0d2c448735a40bb]
-   PD          [Kendall tau Correlation Matrix] [Paper; Kendall's ...] [2010-12-22 08:54:08] [50e0b5177c9c80b42996aa89930b928a] [Current]
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Dataseries X:
108.35	98.68	100.70	104.38	97.72	15.38	31.27
109.87	99.21	99.62	103.97	98.01	15.03	35.83
111.30	99.36	99.83	103.32	97.78	15.21	37.12
115.50	100.72	100.74	105.01	98.04	15.20	36.77
116.22	102.27	100.84	104.88	98.54	14.60	35.17
116.63	102.62	100.85	104.46	98.39	13.79	37.25
116.84	102.97	99.71	104.71	98.58	14.54	33.77
116.63	102.88	100.80	106.09	98.91	14.31	30.59
117.03	102.90	100.06	106.54	98.68	13.93	33.59
117.00	103.01	100.57	104.36	98.59	14.82	37.24
117.14	103.02	99.79	105.31	99.13	14.46	34.81
116.64	103.73	99.90	105.07	98.70	14.85	34.94
117.24	104.18	100.12	105.39	99.00	14.95	34.47
117.52	103.73	100.40	105.65	98.80	14.43	30.48
117.83	103.78	100.51	108.25	98.80	14.84	30.94
119.79	103.61	100.70	107.71	99.29	14.39	30.60
120.86	103.84	100.62	108.58	99.69	15.70	28.42
120.75	103.86	99.70	108.27	100.01	15.34	25.89
120.63	104.14	99.48	107.62	99.85	13.98	26.32
120.89	104.05	99.36	108.80	99.66	14.75	27.18
120.23	104.01	99.39	109.26	101.18	14.81	25.85
121.19	104.49	99.45	108.58	101.47	14.67	26.32
120.79	104.83	99.28	107.05	101.28	15.03	23.07
120.09	104.78	99.40	109.20	101.80	14.34	20.19
120.86	104.95	99.10	109.52	102.48	12.54	18.65
121.10	105.28	99.48	111.12	102.32	11.37	17.74
121.47	105.28	99.74	108.74	102.30	12.58	17.26
122.01	105.91	100.42	110.53	102.84	13.06	16.01
123.94	106.81	100.80	110.44	102.36	12.50	17.94
125.78	106.39	100.66	111.02	102.16	11.11	15.53
125.31	107.02	101.03	111.13	102.57	12.39	14.49
125.79	106.92	101.22	110.90	102.49	12.34	15.35
126.12	107.01	101.23	111.32	104.11	11.54	14.67
125.57	106.79	100.10	109.37	104.78	10.22	12.95
125.44	107.41	99.98	110.18	104.13	8.50	8.81
126.12	107.13	99.91	110.74	104.22	9.06	9.33
126.01	107.54	99.84	111.70	104.73	9.28	9.31
126.50	108.48	99.68	111.33	104.99	7.24	9.03
126.13	108.50	99.74	110.86	104.70	7.58	10.96
126.66	108.27	99.71	109.48	104.69	7.81	14.26
126.33	109.42	99.35	108.77	104.85	8.54	14.20
126.61	110.09	99.21	109.81	104.24	9.27	13.70
126.36	109.98	99.21	109.15	104.74	10.11	17.46
126.83	109.99	99.16	109.63	104.20	9.21	18.73
125.90	109.54	99.20	111.32	105.62	10.71	20.37
126.29	108.85	99.08	109.75	106.08	10.85	18.72
126.37	106.76	98.16	110.37	105.46	11.77	21.60
125.11	107.56	98.00	108.30	105.42	11.81	22.75




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=114115&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=114115&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=114115&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'George Udny Yule' @ 72.249.76.132







Correlations for all pairs of data series (method=kendall)
CoffeeTeaSugarWaterSodaSaraLeeStarbucks
Coffee10.838-0.2660.6420.78-0.655-0.675
Tea0.8381-0.3130.620.814-0.638-0.686
Sugar-0.266-0.3131-0.121-0.3330.1290.133
Water0.6420.62-0.12110.628-0.526-0.699
Soda0.780.814-0.3330.6281-0.609-0.683
SaraLee-0.655-0.6380.129-0.526-0.60910.618
Starbucks-0.675-0.6860.133-0.699-0.6830.6181

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=kendall) \tabularnewline
  & Coffee & Tea & Sugar & Water & Soda & SaraLee & Starbucks \tabularnewline
Coffee & 1 & 0.838 & -0.266 & 0.642 & 0.78 & -0.655 & -0.675 \tabularnewline
Tea & 0.838 & 1 & -0.313 & 0.62 & 0.814 & -0.638 & -0.686 \tabularnewline
Sugar & -0.266 & -0.313 & 1 & -0.121 & -0.333 & 0.129 & 0.133 \tabularnewline
Water & 0.642 & 0.62 & -0.121 & 1 & 0.628 & -0.526 & -0.699 \tabularnewline
Soda & 0.78 & 0.814 & -0.333 & 0.628 & 1 & -0.609 & -0.683 \tabularnewline
SaraLee & -0.655 & -0.638 & 0.129 & -0.526 & -0.609 & 1 & 0.618 \tabularnewline
Starbucks & -0.675 & -0.686 & 0.133 & -0.699 & -0.683 & 0.618 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=114115&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=kendall)[/C][/ROW]
[ROW][C] [/C][C]Coffee[/C][C]Tea[/C][C]Sugar[/C][C]Water[/C][C]Soda[/C][C]SaraLee[/C][C]Starbucks[/C][/ROW]
[ROW][C]Coffee[/C][C]1[/C][C]0.838[/C][C]-0.266[/C][C]0.642[/C][C]0.78[/C][C]-0.655[/C][C]-0.675[/C][/ROW]
[ROW][C]Tea[/C][C]0.838[/C][C]1[/C][C]-0.313[/C][C]0.62[/C][C]0.814[/C][C]-0.638[/C][C]-0.686[/C][/ROW]
[ROW][C]Sugar[/C][C]-0.266[/C][C]-0.313[/C][C]1[/C][C]-0.121[/C][C]-0.333[/C][C]0.129[/C][C]0.133[/C][/ROW]
[ROW][C]Water[/C][C]0.642[/C][C]0.62[/C][C]-0.121[/C][C]1[/C][C]0.628[/C][C]-0.526[/C][C]-0.699[/C][/ROW]
[ROW][C]Soda[/C][C]0.78[/C][C]0.814[/C][C]-0.333[/C][C]0.628[/C][C]1[/C][C]-0.609[/C][C]-0.683[/C][/ROW]
[ROW][C]SaraLee[/C][C]-0.655[/C][C]-0.638[/C][C]0.129[/C][C]-0.526[/C][C]-0.609[/C][C]1[/C][C]0.618[/C][/ROW]
[ROW][C]Starbucks[/C][C]-0.675[/C][C]-0.686[/C][C]0.133[/C][C]-0.699[/C][C]-0.683[/C][C]0.618[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=114115&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=114115&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)
CoffeeTeaSugarWaterSodaSaraLeeStarbucks
Coffee10.838-0.2660.6420.78-0.655-0.675
Tea0.8381-0.3130.620.814-0.638-0.686
Sugar-0.266-0.3131-0.121-0.3330.1290.133
Water0.6420.62-0.12110.628-0.526-0.699
Soda0.780.814-0.3330.6281-0.609-0.683
SaraLee-0.655-0.6380.129-0.526-0.60910.618
Starbucks-0.675-0.6860.133-0.699-0.6830.6181







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
Coffee;Tea0.95430.95510.8378
p-value(0)(0)(0)
Coffee;Sugar-0.2861-0.3916-0.2661
p-value(0.0487)(0.0059)(0.0078)
Coffee;Water0.88090.83170.6424
p-value(0)(0)(0)
Coffee;Soda0.91230.93120.7798
p-value(0)(0)(0)
Coffee;SaraLee-0.8005-0.8414-0.6554
p-value(0)(0)(0)
Coffee;Starbucks-0.8626-0.8611-0.675
p-value(0)(0)(0)
Tea;Sugar-0.3524-0.4326-0.3132
p-value(0.014)(0.0021)(0.0018)
Tea;Water0.80570.81150.6199
p-value(0)(0)(0)
Tea;Soda0.9150.9430.814
p-value(0)(0)(0)
Tea;SaraLee-0.8385-0.8447-0.6383
p-value(0)(0)(0)
Tea;Starbucks-0.824-0.8561-0.6862
p-value(0)(0)(0)
Sugar;Water-0.1779-0.148-0.121
p-value(0.2263)(0.3155)(0.2266)
Sugar;Soda-0.4587-0.473-0.3335
p-value(0.001)(7e-04)(9e-04)
Sugar;SaraLee0.2710.24410.1289
p-value(0.0625)(0.0945)(0.1974)
Sugar;Starbucks0.19580.19020.1325
p-value(0.1823)(0.1952)(0.1853)
Water;Soda0.8340.81830.6276
p-value(0)(0)(0)
Water;SaraLee-0.6916-0.7482-0.5264
p-value(0)(0)(0)
Water;Starbucks-0.9021-0.876-0.6986
p-value(0)(0)(0)
Soda;SaraLee-0.8581-0.828-0.6087
p-value(0)(0)(0)
Soda;Starbucks-0.8845-0.8439-0.6832
p-value(0)(0)(0)
SaraLee;Starbucks0.8460.82690.6176
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
Coffee;Tea & 0.9543 & 0.9551 & 0.8378 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Coffee;Sugar & -0.2861 & -0.3916 & -0.2661 \tabularnewline
p-value & (0.0487) & (0.0059) & (0.0078) \tabularnewline
Coffee;Water & 0.8809 & 0.8317 & 0.6424 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Coffee;Soda & 0.9123 & 0.9312 & 0.7798 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Coffee;SaraLee & -0.8005 & -0.8414 & -0.6554 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Coffee;Starbucks & -0.8626 & -0.8611 & -0.675 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Tea;Sugar & -0.3524 & -0.4326 & -0.3132 \tabularnewline
p-value & (0.014) & (0.0021) & (0.0018) \tabularnewline
Tea;Water & 0.8057 & 0.8115 & 0.6199 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Tea;Soda & 0.915 & 0.943 & 0.814 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Tea;SaraLee & -0.8385 & -0.8447 & -0.6383 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Tea;Starbucks & -0.824 & -0.8561 & -0.6862 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Sugar;Water & -0.1779 & -0.148 & -0.121 \tabularnewline
p-value & (0.2263) & (0.3155) & (0.2266) \tabularnewline
Sugar;Soda & -0.4587 & -0.473 & -0.3335 \tabularnewline
p-value & (0.001) & (7e-04) & (9e-04) \tabularnewline
Sugar;SaraLee & 0.271 & 0.2441 & 0.1289 \tabularnewline
p-value & (0.0625) & (0.0945) & (0.1974) \tabularnewline
Sugar;Starbucks & 0.1958 & 0.1902 & 0.1325 \tabularnewline
p-value & (0.1823) & (0.1952) & (0.1853) \tabularnewline
Water;Soda & 0.834 & 0.8183 & 0.6276 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Water;SaraLee & -0.6916 & -0.7482 & -0.5264 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Water;Starbucks & -0.9021 & -0.876 & -0.6986 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Soda;SaraLee & -0.8581 & -0.828 & -0.6087 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
Soda;Starbucks & -0.8845 & -0.8439 & -0.6832 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
SaraLee;Starbucks & 0.846 & 0.8269 & 0.6176 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=114115&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]Coffee;Tea[/C][C]0.9543[/C][C]0.9551[/C][C]0.8378[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Coffee;Sugar[/C][C]-0.2861[/C][C]-0.3916[/C][C]-0.2661[/C][/ROW]
[ROW][C]p-value[/C][C](0.0487)[/C][C](0.0059)[/C][C](0.0078)[/C][/ROW]
[ROW][C]Coffee;Water[/C][C]0.8809[/C][C]0.8317[/C][C]0.6424[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Coffee;Soda[/C][C]0.9123[/C][C]0.9312[/C][C]0.7798[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Coffee;SaraLee[/C][C]-0.8005[/C][C]-0.8414[/C][C]-0.6554[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Coffee;Starbucks[/C][C]-0.8626[/C][C]-0.8611[/C][C]-0.675[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Tea;Sugar[/C][C]-0.3524[/C][C]-0.4326[/C][C]-0.3132[/C][/ROW]
[ROW][C]p-value[/C][C](0.014)[/C][C](0.0021)[/C][C](0.0018)[/C][/ROW]
[ROW][C]Tea;Water[/C][C]0.8057[/C][C]0.8115[/C][C]0.6199[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Tea;Soda[/C][C]0.915[/C][C]0.943[/C][C]0.814[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Tea;SaraLee[/C][C]-0.8385[/C][C]-0.8447[/C][C]-0.6383[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Tea;Starbucks[/C][C]-0.824[/C][C]-0.8561[/C][C]-0.6862[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Sugar;Water[/C][C]-0.1779[/C][C]-0.148[/C][C]-0.121[/C][/ROW]
[ROW][C]p-value[/C][C](0.2263)[/C][C](0.3155)[/C][C](0.2266)[/C][/ROW]
[ROW][C]Sugar;Soda[/C][C]-0.4587[/C][C]-0.473[/C][C]-0.3335[/C][/ROW]
[ROW][C]p-value[/C][C](0.001)[/C][C](7e-04)[/C][C](9e-04)[/C][/ROW]
[ROW][C]Sugar;SaraLee[/C][C]0.271[/C][C]0.2441[/C][C]0.1289[/C][/ROW]
[ROW][C]p-value[/C][C](0.0625)[/C][C](0.0945)[/C][C](0.1974)[/C][/ROW]
[ROW][C]Sugar;Starbucks[/C][C]0.1958[/C][C]0.1902[/C][C]0.1325[/C][/ROW]
[ROW][C]p-value[/C][C](0.1823)[/C][C](0.1952)[/C][C](0.1853)[/C][/ROW]
[ROW][C]Water;Soda[/C][C]0.834[/C][C]0.8183[/C][C]0.6276[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Water;SaraLee[/C][C]-0.6916[/C][C]-0.7482[/C][C]-0.5264[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Water;Starbucks[/C][C]-0.9021[/C][C]-0.876[/C][C]-0.6986[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Soda;SaraLee[/C][C]-0.8581[/C][C]-0.828[/C][C]-0.6087[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]Soda;Starbucks[/C][C]-0.8845[/C][C]-0.8439[/C][C]-0.6832[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]SaraLee;Starbucks[/C][C]0.846[/C][C]0.8269[/C][C]0.6176[/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=114115&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=114115&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
Coffee;Tea0.95430.95510.8378
p-value(0)(0)(0)
Coffee;Sugar-0.2861-0.3916-0.2661
p-value(0.0487)(0.0059)(0.0078)
Coffee;Water0.88090.83170.6424
p-value(0)(0)(0)
Coffee;Soda0.91230.93120.7798
p-value(0)(0)(0)
Coffee;SaraLee-0.8005-0.8414-0.6554
p-value(0)(0)(0)
Coffee;Starbucks-0.8626-0.8611-0.675
p-value(0)(0)(0)
Tea;Sugar-0.3524-0.4326-0.3132
p-value(0.014)(0.0021)(0.0018)
Tea;Water0.80570.81150.6199
p-value(0)(0)(0)
Tea;Soda0.9150.9430.814
p-value(0)(0)(0)
Tea;SaraLee-0.8385-0.8447-0.6383
p-value(0)(0)(0)
Tea;Starbucks-0.824-0.8561-0.6862
p-value(0)(0)(0)
Sugar;Water-0.1779-0.148-0.121
p-value(0.2263)(0.3155)(0.2266)
Sugar;Soda-0.4587-0.473-0.3335
p-value(0.001)(7e-04)(9e-04)
Sugar;SaraLee0.2710.24410.1289
p-value(0.0625)(0.0945)(0.1974)
Sugar;Starbucks0.19580.19020.1325
p-value(0.1823)(0.1952)(0.1853)
Water;Soda0.8340.81830.6276
p-value(0)(0)(0)
Water;SaraLee-0.6916-0.7482-0.5264
p-value(0)(0)(0)
Water;Starbucks-0.9021-0.876-0.6986
p-value(0)(0)(0)
Soda;SaraLee-0.8581-0.828-0.6087
p-value(0)(0)(0)
Soda;Starbucks-0.8845-0.8439-0.6832
p-value(0)(0)(0)
SaraLee;Starbucks0.8460.82690.6176
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')