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124.06	91.14	83.33	241.66
124.58	88.61	83.33	251.25
122.00	87.34	78.33	230.26
124.02	88.61	77.50	240.91
124.16	87.34	76.67	211.20
124.29	87.34	74.17	188.19
123.93	86.08	72.50	177.01
124.62	88.61	72.50	167.85
121.81	86.08	75.83	174.03
124.14	86.08	71.67	170.09
124.31	84.81	74.17	203.42
125.15	81.01	78.33	254.97
125.35	78.48	85.00	342.84
125.48	77.22	83.33	386.29
124.17	78.48	81.67	440.51
125.33	82.28	83.33	433.58
124.46	83.55	85.00	408.13
123.39	82.28	86.67	370.32
123.14	78.48	90.00	355.51
122.24	78.48	90.00	332.62
119.31	83.55	87.50	314.62
120.87	89.88	89.17	301.73
120.43	92.41	85.83	306.31
119.41	93.67	91.67	282.98
118.85	93.67	90.83	266.48
119.08	93.67	90.83	249.97
117.25	93.67	91.67	259.87
118.51	92.41	93.33	246.24
118.42	92.41	94.17	238.36
118.56	93.67	94.17	238.04
117.97	96.20	91.67	224.19
117.98	96.20	93.33	214.71
115.25	96.20	91.67	203.11
117.23	96.20	85.83	221.00
117.08	98.74	93.33	211.73
116.83	100.00	94.17	209.39
117.17	102.53	90.83	217.48
117.73	103.80	90.83	242.19
115.74	103.80	90.83	244.64
116.99	102.53	90.83	232.07
116.90	102.53	87.50	235.80
116.49	102.53	89.17	230.37
115.84	102.53	88.33	209.82
115.92	102.53	90.83	206.41
113.32	103.80	91.67	209.60
114.84	105.07	88.33	192.24
114.75	106.33	85.00	186.17
114.84	107.60	85.83	193.41
115.03	108.86	80.83	202.36
115.03	107.60	84.17	203.00
112.99	105.07	83.33	190.64
114.15	98.74	83.33	185.43
113.77	98.74	83.33	171.58
113.57	101.27	88.33	179.57
113.38	108.86	90.83	180.42
112.71	112.66	90.00	162.10
110.27	112.66	87.50	157.95
111.73	108.86	87.50	146.66
112.12	105.07	86.67	154.43
112.31	105.07	87.50	163.38
111.73	105.07	90.83	150.92
111.83	106.33	90.83	151.98
109.99	107.60	89.17	144.74
111.15	106.33	92.50	140.37
111.25	108.86	87.50	143.36
110.87	107.60	89.17	135.79
110.27	107.60	90.00	134.73
110.18	106.33	91.67	126.42
108.15	107.60	90.00	124.72
109.60	107.60	87.50	117.90
109.60	107.60	87.50	114.07
109.41	107.60	80.00	112.26
109.80	107.60	88.33	105.44
109.60	107.60	83.33	110.77
107.76	107.60	81.67	107.68
109.02	107.60	84.17	105.76
108.62	108.86	85.00	102.03
109.02	106.33	83.33	100.22
109.22	102.53	77.50	111.62
108.92	101.27	81.67	118.11
106.69	101.27	85.00	111.72
107.76	101.27	85.83	103.42
107.66	101.27	89.17	97.13
107.85	100.00	90.00	103.10
107.95	98.74	90.00	104.91
107.85	98.74	90.00	100.22
106.30	100.00	91.67	98.52
107.37	102.53	92.50	95.32
107.66	101.27	93.33	96.92
107.46	96.20	92.50	96.60
107.37	92.41	94.17	92.55
107.18	88.61	93.33	82.75
105.43	86.08	91.67	80.84
106.39	88.61	85.83	79.13
106.50	89.88	77.50	79.77
106.50	91.14	80.83	85.10
106.69	89.88	89.17	96.39
106.50	87.34	92.50	97.56
105.14	84.81	95.83	96.39
106.50	84.81	95.83	101.18
106.20	83.55	95.00	103.52
105.72	87.34	95.00	100.11
104.76	92.41	98.33	99.26
104.55	94.94	99.17	104.48
102.71	92.41	103.33	101.29
104.36	89.88	105.00	100.33
104.65	87.34	104.17	115.24
104.46	89.88	104.17	113.64
104.65	94.94	100.83	115.35
103.88	97.47	105.83	108.42
102.32	98.74	103.33	105.65
103.39	98.74	105.00	108.64
103.00	97.47	103.33	104.80
102.71	98.74	102.50	95.43
102.51	98.74	103.33	104.48
102.04	100.00	101.67	103.84
100.00	100.00	100.00	100.01

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='kendall')
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$counts; y <- y/max(y)
rect(breaks[-nB], 0, breaks[-1], y, col='grey', ...)
}
bitmap(file='test1.png')
pairs(t(y),diag.panel=panel.hist, upper.panel=panel.smooth, lower.panel=panel.tau, main=main)
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Kendall tau rank correlations for all pairs of data series',3,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'pair',1,TRUE)
a<-table.element(a,'tau',1,TRUE)
a<-table.element(a,'p-value',1,TRUE)
a<-table.row.end(a)
n <- length(y[,1])
n
cor.test(y[1,],y[2,],method='kendall')
for (i in 1:(n-1))
{
for (j in (i+1):n)
{
a<-table.row.start(a)
dum <- paste('tau(',dimnames(t(x))[[2]][i])
dum <- paste(dum,',')
dum <- paste(dum,dimnames(t(x))[[2]][j])
dum <- paste(dum,')')
a<-table.element(a,dum,header=TRUE)
r <- cor.test(y[i,],y[j,],method='kendall')
a<-table.element(a,r$estimate)
a<-table.element(a,r$p.value)
a<-table.row.end(a)
}
}
a<-table.end(a)
table.save(a,file='mytable.tab')