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*The author of this computation has been verified*

R Software Module

rwasp_pairs.wasp

Title produced by software

Kendall tau Correlation Matrix

Date of computation

Sun, 18 Dec 2011 10:22:22 -0500

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Dec/18/t1324221765mrgrcnlvmj2gxdg.htm/, Retrieved Sun, 05 May 2024 09:32:17 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=156972, Retrieved Sun, 05 May 2024 09:32:17 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

122

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-       [Kendall tau Correlation Matrix] [pearson correlati...] [2011-12-18 15:22:22] [55f9d13d4d3dd59c775a5501608cd0fe] [Current]
-    D    [Kendall tau Correlation Matrix] [Pearson Correlati...] [2011-12-21 11:32:18] [2c6fcdc40ef3b1a27716d75d6f478b32] 
- R         [Kendall tau Correlation Matrix] [] [2011-12-22 10:26:10] [4f851df07e928502141e501e960f13e4] 
-    D    [Kendall tau Correlation Matrix] [Pearson Correlati...] [2011-12-21 12:34:57] [8e7c659e1b71a02d35eacc5210237549] 
-   PD    [Kendall tau Correlation Matrix] [Kendall tau Corre...] [2011-12-21 13:00:56] [8e7c659e1b71a02d35eacc5210237549] 
-   PD    [Kendall tau Correlation Matrix] [Kendall tau Corre...] [2011-12-21 13:00:56] [8e7c659e1b71a02d35eacc5210237549] 
-   PD    [Kendall tau Correlation Matrix] [Kendall's tau Cor...] [2011-12-21 13:14:26] [2c6fcdc40ef3b1a27716d75d6f478b32] 
- RM        [Kendall tau Correlation Matrix] [] [2011-12-22 10:27:22] [4f851df07e928502141e501e960f13e4] 
- RMPD    [Multiple Regression] [Multiple Regression] [2011-12-21 13:40:30] [2c6fcdc40ef3b1a27716d75d6f478b32] 
- RMP       [Recursive Partitioning (Regression Trees)] [Recursive Partiti...] [2011-12-21 14:30:18] [2c6fcdc40ef3b1a27716d75d6f478b32] 
- RMP         [Recursive Partitioning (Regression Trees)] [] [2011-12-22 10:31:01] [4f851df07e928502141e501e960f13e4] 
- RM        [Multiple Regression] [] [2011-12-22 10:27:58] [4f851df07e928502141e501e960f13e4] 

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Dataseries X:

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157382	48	18	20465	23975	0
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221399	76	30	54002	72255	0
454489	118	36	151036	189748	1
134379	42	23	33287	61834	1
150416	62	30	31172	68167	0
121391	48	30	28113	38462	0
275326	67	26	57803	101219	1
121593	50	24	49830	43270	2
172071	71	30	52143	76183	0
86249	41	21	21055	31476	0
201902	77	25	47007	62157	4
144113	45	17	28735	46261	4
144677	54	19	59147	50063	3
134153	75	33	78950	64483	0
64149	0	15	13497	2341	5
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27918	13	18	53249	12743	0
52197	16	15	10726	18743	0
191463	78	27	83700	97057	0
176034	35	25	40400	17675	0
98629	38	34	33797	33106	1
143546	50	21	36205	53311	1
139780	39	21	30165	42754	0
174181	58	25	58534	59056	0
163773	70	28	44663	101621	0
312831	55	28	92556	118120	0
184024	52	20	40078	79572	0
151621	50	28	34711	42744	0
164516	54	20	31076	65931	2
120414	53	17	74608	38575	4
214975	76	25	58092	28795	0
200609	54	24	42009	94440	1
0	0	0	0	0	0
191923	46	27	36022	38229	0
93107	44	14	23333	31972	3
129419	35	32	53349	40071	9
233497	82	31	92596	132480	0
178228	73	21	49598	62797	2
126602	31	34	44093	40429	0
94332	25	23	84205	45545	2
164183	57	24	63369	57568	1
95704	44	22	60132	39019	2
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81293	23	35	24460	38345	1
189007	63	21	46456	50210	0
173779	43	31	66616	80947	1
146552	62	26	41554	43461	7
48188	12	22	22346	14812	0
113870	67	21	30874	37819	0
266451	60	27	68701	102738	0
229437	55	26	35728	54509	0
174876	53	33	29010	62956	1
119070	35	11	23110	55411	6
186704	50	26	38844	50611	0
72559	25	26	27084	26692	0
111940	47	23	35139	60056	0
166226	30	38	57476	25155	10
135901	50	29	33277	42840	6
102141	36	19	31141	39358	0
115753	43	19	61281	47241	11
102194	44	24	25820	49611	3
148531	25	26	23284	41833	0
94982	38	29	35378	48930	0
178613	68	36	74990	110600	8
128907	83	25	29653	52235	2
102378	48	24	64622	53986	0
31970	5	21	4157	4105	0
204812	53	19	29245	59331	3
104972	36	12	50008	47796	1
95276	62	28	52338	38302	2
101560	46	21	13310	14063	1
144193	67	34	92901	54414	0
71921	2	32	10956	9903	2
126905	64	27	34241	53987	1
140303	59	28	75043	88937	0
60138	16	21	21152	21928	0
84971	34	31	42249	29487	0
80420	54	26	42005	35334	0
244190	39	29	41152	57596	0
56252	26	23	14399	29750	0
97181	37	25	28263	41029	0
50913	17	22	17215	12416	0
143910	32	26	48140	51158	0
218900	55	33	62897	79935	0
90772	50	22	22883	26552	0
90385	39	24	41622	25807	6
136220	30	21	40715	50620	0
115572	45	28	65897	61467	5
139075	66	23	76542	65292	1
148950	39	25	37477	55516	0
124626	27	15	53216	42006	0
49176	22	13	40911	26273	0
215480	45	36	57021	90248	0
182328	95	24	73116	61476	0
19349	13	1	3895	9604	0
183873	26	24	46609	45108	3
146020	40	31	29351	47232	0
51201	13	4	2325	3439	0
58280	41	20	31747	30553	0
115944	51	23	32665	24751	0
101515	27	23	19249	34458	1
72904	30	12	15292	24649	0
27676	2	16	5842	2342	0
131173	79	29	33994	52739	0
89920	12	10	13018	6245	0
0	0	0	0	0	0
85610	46	25	98177	35381	0
106742	25	21	37941	19595	0
126825	49	23	31032	50848	0
109807	52	21	32683	39443	0
71894	36	21	34545	27023	0
3616	0	0	0	0	0
0	0	0	0	0	0
154806	35	23	27525	61022	0
136333	68	29	66856	63528	0
147766	26	28	28549	34835	1
113245	36	23	38610	37172	0
43410	7	1	2781	13	0
152455	67	25	41211	62548	1
88874	30	17	22698	31334	0
111924	55	29	41194	20839	8
60373	3	12	32689	5084	3
19764	10	2	5752	9927	1
125760	46	20	26757	53229	2
108685	23	25	22527	29877	0
141868	48	29	44810	37310	0
11796	1	2	0	0	0
10674	0	0	0	0	0
131263	33	18	100674	50067	0
6836	0	1	0	0	0
153278	48	21	57786	47708	5
5118	5	0	0	0	0
40248	8	4	5444	6012	1
0	0	0	0	0	0
100798	25	25	28470	27749	0
84315	21	26	61849	47555	0
7131	0	0	0	0	1
8812	0	4	2179	1336	0
63952	15	17	8019	11017	1
120111	47	21	39644	55184	0
94127	17	22	23494	43485	1

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	'Gertrude Mary Cox' @ cox.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 & 1 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=156972&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=156972&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=156972&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 Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	'Gertrude Mary Cox' @ cox.wessa.net

Correlations for all pairs of data series (method=pearson)
	time	blogs	reviews	CWcharacters	CWseconds	shared
time	1	0.784	0.666	0.703	0.864	0.095
blogs	0.784	1	0.657	0.702	0.787	0.098
reviews	0.666	0.657	1	0.618	0.622	0.149
CWcharacters	0.703	0.702	0.618	1	0.756	0.156
CWseconds	0.864	0.787	0.622	0.756	1	0.051
shared	0.095	0.098	0.149	0.156	0.051	1

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & time & blogs & reviews & CWcharacters & CWseconds & shared \tabularnewline
time & 1 & 0.784 & 0.666 & 0.703 & 0.864 & 0.095 \tabularnewline
blogs & 0.784 & 1 & 0.657 & 0.702 & 0.787 & 0.098 \tabularnewline
reviews & 0.666 & 0.657 & 1 & 0.618 & 0.622 & 0.149 \tabularnewline
CWcharacters & 0.703 & 0.702 & 0.618 & 1 & 0.756 & 0.156 \tabularnewline
CWseconds & 0.864 & 0.787 & 0.622 & 0.756 & 1 & 0.051 \tabularnewline
shared & 0.095 & 0.098 & 0.149 & 0.156 & 0.051 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=156972&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]time[/C][C]blogs[/C][C]reviews[/C][C]CWcharacters[/C][C]CWseconds[/C][C]shared[/C][/ROW]
[ROW][C]time[/C][C]1[/C][C]0.784[/C][C]0.666[/C][C]0.703[/C][C]0.864[/C][C]0.095[/C][/ROW]
[ROW][C]blogs[/C][C]0.784[/C][C]1[/C][C]0.657[/C][C]0.702[/C][C]0.787[/C][C]0.098[/C][/ROW]
[ROW][C]reviews[/C][C]0.666[/C][C]0.657[/C][C]1[/C][C]0.618[/C][C]0.622[/C][C]0.149[/C][/ROW]
[ROW][C]CWcharacters[/C][C]0.703[/C][C]0.702[/C][C]0.618[/C][C]1[/C][C]0.756[/C][C]0.156[/C][/ROW]
[ROW][C]CWseconds[/C][C]0.864[/C][C]0.787[/C][C]0.622[/C][C]0.756[/C][C]1[/C][C]0.051[/C][/ROW]
[ROW][C]shared[/C][C]0.095[/C][C]0.098[/C][C]0.149[/C][C]0.156[/C][C]0.051[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=156972&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=156972&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)
	time	blogs	reviews	CWcharacters	CWseconds	shared
time	1	0.784	0.666	0.703	0.864	0.095
blogs	0.784	1	0.657	0.702	0.787	0.098
reviews	0.666	0.657	1	0.618	0.622	0.149
CWcharacters	0.703	0.702	0.618	1	0.756	0.156
CWseconds	0.864	0.787	0.622	0.756	1	0.051
shared	0.095	0.098	0.149	0.156	0.051	1

Correlations for all pairs of data series with p-values
pair	Pearson r	Spearman rho	Kendall tau
time;blogs	0.7839	0.7567	0.5793
p-value	(0)	(0)	(0)
time;reviews	0.6656	0.5831	0.4272
p-value	(0)	(0)	(0)
time;CWcharacters	0.703	0.6484	0.4877
p-value	(0)	(0)	(0)
time;CWseconds	0.8643	0.8234	0.6565
p-value	(0)	(0)	(0)
time;shared	0.0947	0.14	0.1067
p-value	(0.2586)	(0.0942)	(0.0954)
blogs;reviews	0.6567	0.5597	0.4141
p-value	(0)	(0)	(0)
blogs;CWcharacters	0.7018	0.6657	0.5008
p-value	(0)	(0)	(0)
blogs;CWseconds	0.787	0.7699	0.597
p-value	(0)	(0)	(0)
blogs;shared	0.0979	0.1327	0.1005
p-value	(0.243)	(0.113)	(0.1191)
reviews;CWcharacters	0.6177	0.5678	0.4237
p-value	(0)	(0)	(0)
reviews;CWseconds	0.6223	0.5583	0.4166
p-value	(0)	(0)	(0)
reviews;shared	0.1488	0.0379	0.0286
p-value	(0.0751)	(0.6521)	(0.6617)
CWcharacters;CWseconds	0.7563	0.7017	0.5394
p-value	(0)	(0)	(0)
CWcharacters;shared	0.1556	0.1545	0.118
p-value	(0.0626)	(0.0644)	(0.0655)
CWseconds;shared	0.0511	0.149	0.107
p-value	(0.5428)	(0.0747)	(0.0949)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
time;blogs & 0.7839 & 0.7567 & 0.5793 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
time;reviews & 0.6656 & 0.5831 & 0.4272 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
time;CWcharacters & 0.703 & 0.6484 & 0.4877 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
time;CWseconds & 0.8643 & 0.8234 & 0.6565 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
time;shared & 0.0947 & 0.14 & 0.1067 \tabularnewline
p-value & (0.2586) & (0.0942) & (0.0954) \tabularnewline
blogs;reviews & 0.6567 & 0.5597 & 0.4141 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
blogs;CWcharacters & 0.7018 & 0.6657 & 0.5008 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
blogs;CWseconds & 0.787 & 0.7699 & 0.597 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
blogs;shared & 0.0979 & 0.1327 & 0.1005 \tabularnewline
p-value & (0.243) & (0.113) & (0.1191) \tabularnewline
reviews;CWcharacters & 0.6177 & 0.5678 & 0.4237 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
reviews;CWseconds & 0.6223 & 0.5583 & 0.4166 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
reviews;shared & 0.1488 & 0.0379 & 0.0286 \tabularnewline
p-value & (0.0751) & (0.6521) & (0.6617) \tabularnewline
CWcharacters;CWseconds & 0.7563 & 0.7017 & 0.5394 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
CWcharacters;shared & 0.1556 & 0.1545 & 0.118 \tabularnewline
p-value & (0.0626) & (0.0644) & (0.0655) \tabularnewline
CWseconds;shared & 0.0511 & 0.149 & 0.107 \tabularnewline
p-value & (0.5428) & (0.0747) & (0.0949) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=156972&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]time;blogs[/C][C]0.7839[/C][C]0.7567[/C][C]0.5793[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]time;reviews[/C][C]0.6656[/C][C]0.5831[/C][C]0.4272[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]time;CWcharacters[/C][C]0.703[/C][C]0.6484[/C][C]0.4877[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]time;CWseconds[/C][C]0.8643[/C][C]0.8234[/C][C]0.6565[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]time;shared[/C][C]0.0947[/C][C]0.14[/C][C]0.1067[/C][/ROW]
[ROW][C]p-value[/C][C](0.2586)[/C][C](0.0942)[/C][C](0.0954)[/C][/ROW]
[ROW][C]blogs;reviews[/C][C]0.6567[/C][C]0.5597[/C][C]0.4141[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]blogs;CWcharacters[/C][C]0.7018[/C][C]0.6657[/C][C]0.5008[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]blogs;CWseconds[/C][C]0.787[/C][C]0.7699[/C][C]0.597[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]blogs;shared[/C][C]0.0979[/C][C]0.1327[/C][C]0.1005[/C][/ROW]
[ROW][C]p-value[/C][C](0.243)[/C][C](0.113)[/C][C](0.1191)[/C][/ROW]
[ROW][C]reviews;CWcharacters[/C][C]0.6177[/C][C]0.5678[/C][C]0.4237[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]reviews;CWseconds[/C][C]0.6223[/C][C]0.5583[/C][C]0.4166[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]reviews;shared[/C][C]0.1488[/C][C]0.0379[/C][C]0.0286[/C][/ROW]
[ROW][C]p-value[/C][C](0.0751)[/C][C](0.6521)[/C][C](0.6617)[/C][/ROW]
[ROW][C]CWcharacters;CWseconds[/C][C]0.7563[/C][C]0.7017[/C][C]0.5394[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]CWcharacters;shared[/C][C]0.1556[/C][C]0.1545[/C][C]0.118[/C][/ROW]
[ROW][C]p-value[/C][C](0.0626)[/C][C](0.0644)[/C][C](0.0655)[/C][/ROW]
[ROW][C]CWseconds;shared[/C][C]0.0511[/C][C]0.149[/C][C]0.107[/C][/ROW]
[ROW][C]p-value[/C][C](0.5428)[/C][C](0.0747)[/C][C](0.0949)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=156972&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=156972&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
pair	Pearson r	Spearman rho	Kendall tau
time;blogs	0.7839	0.7567	0.5793
p-value	(0)	(0)	(0)
time;reviews	0.6656	0.5831	0.4272
p-value	(0)	(0)	(0)
time;CWcharacters	0.703	0.6484	0.4877
p-value	(0)	(0)	(0)
time;CWseconds	0.8643	0.8234	0.6565
p-value	(0)	(0)	(0)
time;shared	0.0947	0.14	0.1067
p-value	(0.2586)	(0.0942)	(0.0954)
blogs;reviews	0.6567	0.5597	0.4141
p-value	(0)	(0)	(0)
blogs;CWcharacters	0.7018	0.6657	0.5008
p-value	(0)	(0)	(0)
blogs;CWseconds	0.787	0.7699	0.597
p-value	(0)	(0)	(0)
blogs;shared	0.0979	0.1327	0.1005
p-value	(0.243)	(0.113)	(0.1191)
reviews;CWcharacters	0.6177	0.5678	0.4237
p-value	(0)	(0)	(0)
reviews;CWseconds	0.6223	0.5583	0.4166
p-value	(0)	(0)	(0)
reviews;shared	0.1488	0.0379	0.0286
p-value	(0.0751)	(0.6521)	(0.6617)
CWcharacters;CWseconds	0.7563	0.7017	0.5394
p-value	(0)	(0)	(0)
CWcharacters;shared	0.1556	0.1545	0.118
p-value	(0.0626)	(0.0644)	(0.0655)
CWseconds;shared	0.0511	0.149	0.107
p-value	(0.5428)	(0.0747)	(0.0949)

Figure 1

PNG link

Postscript link

PDF link

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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code