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11.5	8	350	165	3693
11	8	318	150	3436
10.5	8	302	140	3449
10	8	429	198	4341
8.5	8	440	215	4312
10	8	455	225	4425
10	8	383	170	3563
8	8	340	160	3609
10	8	455	225	3086
15	4	113	95	2372
15.5	6	199	97	2774
20.5	4	97	46	1835
17.5	4	110	87	2672
17.5	4	104	95	2375
12.5	4	121	113	2234
14	8	360	215	4615
15	8	307	200	4376
18.5	8	304	193	4732
14.5	4	97	88	2130
14	4	113	95	2228
15.5	6	250	100	3329
15.5	6	232	100	3288
12	8	350	165	4209
13	8	318	150	4096
12	8	400	170	4746
12	8	400	175	5140
19	4	140	72	2408
15	6	250	100	3282
14	4	122	86	2220
14	4	116	90	2123
14.5	4	88	76	2065
19	4	71	65	1773
19	4	97	60	1834
20.5	4	91	70	1955
17	4	97.5	80	2126
16.5	4	122	86	2226
12	8	350	165	4274
13.5	8	318	150	4135
13	8	351	153	4129
11	8	429	208	4633
13.5	8	350	155	4502
12.5	8	400	190	4422
13.5	3	70	97	2330
14	8	307	130	4098
16	8	302	140	4294
14.5	4	121	112	2933
18	4	121	76	2511
16	4	122	86	2395
14.5	4	120	97	2506
15	4	98	80	2164
13	8	350	175	4100
11.5	8	304	150	3672
14.5	8	302	137	4042
12.5	8	318	150	3777
12	8	400	150	4464
13	8	351	158	4363
11	8	440	215	4735
11	8	455	225	4951
16.5	6	225	105	3121
18	6	250	100	3278
16.5	6	250	88	3021
16	6	198	95	2904
14	8	400	150	4997
12.5	8	350	180	4499
15	6	232	100	2789
19.5	4	140	72	2401
16.5	4	108	94	2379
18.5	4	122	85	2310
14	6	155	107	2472
13	8	350	145	4082
9.5	8	400	230	4278
15.5	4	116	75	2158
14	4	114	91	2582
11	8	318	150	3399
14	4	121	110	2660
11	8	350	180	3664
16.5	6	198	95	3102
16	6	232	100	2901
16.5	4	122	80	2451
21	4	71	65	1836
17	6	250	100	3781
18	6	258	110	3632
14	8	302	140	4141
14.5	8	350	150	4699
16	8	302	140	4638
15.5	8	304	150	4257
15.5	4	79	67	1963
14.5	4	97	78	2300
19	4	83	61	2003
14.5	4	90	75	2125
14	4	116	75	2246
15	4	120	97	2489
16	4	79	67	2000
16	6	225	95	3264
19.5	6	250	72	3158
11.5	8	400	170	4668
14	8	350	145	4440
13.5	8	351	148	4657
21	6	231	110	3907
19	6	258	110	3730
19	6	225	95	3785
13.5	8	262	110	3221
12	8	302	129	3169
17	4	140	83	2639
16	6	232	100	2914
13.5	4	134	96	2702
16.5	4	90	71	2223
14.5	6	171	97	2984
15	4	115	95	2694
17	4	120	88	2957
13.5	4	121	115	2671
17.5	4	91	53	1795
16.9	4	116	81	2220
14.9	4	140	92	2572
15.3	4	101	83	2202
13	8	305	140	4215
13.9	8	304	120	3962
12.8	8	351	152	4215
14.5	6	250	105	3353
17.6	6	200	81	3012
22.2	4	85	52	2035
22.1	4	98	60	2164
17.7	6	225	100	3651
16.2	6	250	110	3645
17.8	6	258	95	3193
17	4	85	70	1990
16.4	4	97	75	2155
15.7	4	130	102	3150
13.2	8	318	150	3940
16.7	6	168	120	3820
12.1	8	350	180	4380
15	8	302	130	3870
14	8	318	150	3755
14.8	4	111	80	2155
18.6	4	79	58	1825
16.8	4	85	70	1945
12.5	8	305	145	3880
13.7	8	318	145	4140
16.9	6	231	105	3425
17.7	6	225	100	3630
11.1	8	400	180	4220
11.4	8	350	170	4165
14.5	8	351	149	4335
14.5	4	97	78	1940
18.2	4	97	75	2265
15.8	4	140	89	2755
15.9	4	98	83	2075
16.4	4	97	67	1985
14.5	6	146	97	2815
12.8	4	121	110	2600
21.5	4	90	48	1985
14.4	4	98	66	1800
18.6	4	85	70	2070
13.2	8	318	140	3735
12.8	8	302	139	3570
18.2	6	200	95	3155
15.8	6	200	85	2965
17.2	6	225	100	3430
17.2	6	232	90	3210
16.7	6	200	85	3070
18.7	6	225	110	3620
13.2	8	305	145	3425
13.4	6	231	165	3445
13.7	8	318	140	4080
16.5	4	98	68	2155
14.7	4	119	97	2300
14.5	4	105	75	2230
17.6	4	151	85	2855
15.9	5	131	103	2830
13.6	6	163	125	3140
15.8	6	163	133	3410
14.9	4	89	71	1990
16.6	4	98	68	2135
18.2	6	200	85	2990
17.3	4	140	88	2890
16.6	6	225	110	3360
15.4	8	305	130	3840
13.2	8	351	138	3955
15.2	8	318	135	3830
14.3	8	351	142	4054
15	8	267	125	3605
14	4	89	71	1925
15.2	4	86	65	1975
15	4	121	80	2670
24.8	4	141	71	3190
22.2	8	260	90	3420
14.9	4	105	70	2150
19.2	4	85	65	2020
16	4	151	90	2670
11.3	6	173	115	2595
13.2	4	151	90	2556
14.7	4	98	76	2144
15.5	4	98	70	2120
16.4	4	86	65	2019
18.1	4	140	88	2870
20.1	4	151	90	3003
15.8	4	97	78	2188
15.5	4	134	90	2711
15	4	119	92	2434
15.2	4	108	75	2265
14.4	4	156	105	2800
19.2	4	85	65	2110
19.9	5	121	67	2950
13.8	4	91	67	1850
15.3	4	89	62	1845
15.1	4	122	88	2500
15.7	4	135	84	2490
16.4	4	151	84	2635
12.6	6	173	110	2725
12.9	4	135	84	2385
16.4	4	86	64	1875
16.1	4	81	60	1760
19.4	4	85	65	1975
17.3	4	89	62	2050
14.9	4	105	63	2215
16.2	4	98	65	2045
14.2	4	105	74	2190
14.8	4	119	100	2615
20.4	4	141	80	3230
13.8	6	146	120	2930
15.8	6	231	110	3415
17.1	6	200	88	3060
16.6	6	225	85	3465
18.6	4	112	88	2640
18	4	112	88	2395
16	4	135	84	2525
18	4	151	90	2735
15.3	4	105	74	1980
17.6	4	91	68	1970
14.7	4	105	63	2125
14.5	4	120	88	2160
14.5	4	107	75	2205
15.7	4	91	67	1965
16.4	6	181	110	2945
17	6	262	85	3015
13.9	4	144	96	2665
17.3	4	151	90	2950
15.6	4	140	86	2790
11.6	4	135	84	2295
18.6	4	120	79	2625

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')