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89	81	83	95	81	83
90	91	102	87	90	102
82	96	75	91	91	75
82	85	92	84	87	92
71	74	94	92	89	94
80	78	88	84	85	88
62	71	77	84	81	77
77	72	63	69	80	63
80	87	73	84	75	73
87	72	85	84	84	85
96	90	80	85	91	80
80	87	77	89	87	77
85	89	67	83	90	67
89	110	98	86	72	98
89	95	89	91	96	89
73	72	63	90	88	63
88	70	97	77	73	97
86	79	77	88	86	77
83	92	96	88	67	96
91	93	84	88	89	84
98	97	94	102	94	94
80	75	70	103	88	70
84	88	100	84	77	100
90	105	88	87	89	88
92	82	97	88	104	97
86	89	78	93	89	78
117	114	108	101	107	108
88	81	81	88	96	81
86	73	96	113	111	96
78	82	84	95	84	84
104	110	104	99	83	104
89	93	87	85	82	87
99	114	98	105	105	98
84	91	89	105	100	89
89	97	93	96	111	93
95	97	89	88	90	89
58	68	63	93	87	63
77	72	84	93	90	84
77	81	82	69	67	82
98	102	105	83	84	105
58	62	70	83	84	70
81	102	94	93	96	94
92	84	101	69	67	101
94	75	83	86	90	83
87	102	88	90	83	88
75	62	69	87	78	69
80	100	94	92	100	94
84	82	82	75	67	82
87	78	82	89	94	82
114	106	109	88	89	109
97	88	86	87	89	86
102	85	99	113	111	99
80	97	82	102	88	82
112	114	114	101	94	114
104	105	99	87	111	99
75	100	91	105	111	91
82	72	81	101	105	81
92	106	102	79	97	102
102	78	101	86	83	101
73	80	72	95	105	72
78	88	91	104	69	91
74	62	83	79	80	83
92	93	102	86	87	102
97	87	103	81	67	103
92	109	93	92	92	93
91	91	88	95	102	88
102	110	110	97	90	110
89	98	100	87	98	100
98	99	88	94	94	88
117	95	119	105	101	119
92	97	98	94	96	98
70	88	90	88	94	90
63	72	69	105	105	69
91	102	98	113	105	98
106	95	98	69	84	98
81	93	81	69	72	81
98	90	93	100	96	93
88	80	91	113	94	91
95	75	86	88	107	86
105	109	95	104	103	95
90	75	87	94	95	87
58	72	63	91	73	63
86	77	89	103	110	89
112	93	108	95	84	108
71	72	99	69	67	99
98	91	90	86	73	90
87	95	91	108	84	91
98	111	82	83	79	82
117	105	119	102	91	119
98	90	97	94	92	97
98	105	108	113	107	108
90	90	101	113	111	101
84	92	96	93	89	96
86	95	97	105	110	97
68	75	69	88	98	69
86	92	89	90	95	89
77	100	84	92	84	84
83	82	79	81	73	79
90	102	103	86	86	103
107	104	92	85	98	92
102	98	104	86	90	104
90	95	102	97	97	102
113	114	106	103	106	106
86	93	93	102	106	93
105	110	108	NA	NA	108
110	104	119	NA	NA	119
82	91	102	NA	NA	102
89	79	83	NA	NA	83
99	97	92	NA	NA	92
113	102	119	NA	NA	119
91	77	100	NA	NA	100
92	105	97	NA	NA	97
86	95	103	NA	NA	103
91	104	95	NA	NA	95
82	75	73	NA	NA	73
86	82	86	NA	NA	86
86	91	88	NA	NA	88
102	105	102	NA	NA	102
84	71	87	NA	NA	87
80	89	100	NA	NA	100
96	79	88	NA	NA	88
117	113	100	NA	NA	100
88	82	79	NA	NA	79
99	102	90	NA	NA	90
89	82	83	NA	NA	83
86	92	95	NA	NA	95
98	82	89	NA	NA	89
58	86	64	NA	NA	64
98	108	108	NA	NA	108
58	74	80	NA	NA	80
81	87	83	NA	NA	83
90	97	96	NA	NA	96
112	102	108	NA	NA	108
84	75	86	NA	NA	86
84	82	88	NA	NA	88
75	72	97	NA	NA	97
78	88	110	NA	NA	110
94	97	102	NA	NA	102
75	85	92	NA	NA	92
82	62	91	NA	NA	91
87	95	92	NA	NA	92
59	95	72	NA	NA	72
68	72	88	NA	NA	88
80	92	99	NA	NA	99
94	91	95	NA	NA	95
87	97	83	NA	NA	83
70	78	68	NA	NA	68
113	95	101	NA	NA	101
99	91	91	NA	NA	91
90	95	89	NA	NA	89
102	88	98	NA	NA	98
80	92	89	NA	NA	89
98	97	98	NA	NA	98
98	104	97	NA	NA	97
95	113	98	NA	NA	98
104	113	113	NA	NA	113
86	82	83	NA	NA	83
84	90	92	NA	NA	92
85	91	113	NA	NA	113
90	95	103	NA	NA	103
86	102	96	NA	NA	96
97	92	94	NA	NA	94

par1 <- as.numeric(par1) #colour
par2<- as.logical(par2) # Notches ?
par3<-as.numeric(par3) # % trim
if(par3>45){par3<-45;warning('trim limited to 45%')}
if(par3<0){par3<-0;warning('negative trim makes no sense. Trim is zero.')}
lotrm<-as.integer(length(y[1,])*par3/100)+1
hitrm<-as.integer(length(y[1,])*(100-par3)/100)
y1<-array(dim=c(dim(y)[1], hitrm-lotrm+1), dimnames=list(dimnames(y)[[1]], 1:(hitrm-lotrm+1) ))
for(i in 1:dim(y)[1]){
tmp<-order(y[i,])
y1[i,]<- y[i, tmp[lotrm:hitrm] ]
}
bitmap(file='test2.png')
pairs(t(y))
dev.off()
y<-y1
z <- as.data.frame(t(y))
bitmap(file='test1.png')
(r<-boxplot(z ,xlab=xlab,ylab=ylab,main=main,notch=par2,col=par1))
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('overview.htm','Boxplot statistics','Boxplot overview'),6,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',1,TRUE)
a<-table.element(a,hyperlink('lower_whisker.htm','lower whisker','definition of lower whisker'),1,TRUE)
a<-table.element(a,hyperlink('lower_hinge.htm','lower hinge','definition of lower hinge'),1,TRUE)
a<-table.element(a,hyperlink('central_tendency.htm','median','definitions about measures of central tendency'),1,TRUE)
a<-table.element(a,hyperlink('upper_hinge.htm','upper hinge','definition of upper hinge'),1,TRUE)
a<-table.element(a,hyperlink('upper_whisker.htm','upper whisker','definition of upper whisker'),1,TRUE)
a<-table.row.end(a)
for (i in 1:length(y[,1]))
{
a<-table.row.start(a)
a<-table.element(a,dimnames(t(x))[[2]][i],1,TRUE)
for (j in 1:5)
{
a<-table.element(a,round(r$stats[j,i], digits=2))
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
if (par2){
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Boxplot Notches',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',1,TRUE)
a<-table.element(a,'lower bound',1,TRUE)
a<-table.element(a,'median',1,TRUE)
a<-table.element(a,'upper bound',1,TRUE)
a<-table.row.end(a)
for (i in 1:length(y[,1]))
{
a<-table.row.start(a)
a<-table.element(a,dimnames(t(x))[[2]][i],1,TRUE)
a<-table.element(a,round(r$conf[1,i], digits=2))
a<-table.element(a, round(r$stats[3,i], digits=2))
a<-table.element(a,round(r$conf[2,i], digits=2))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')
}
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Boxplot Means',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',1,TRUE)
a<-table.element(a,hyperlink('trimmed_mean.htm','trimmed mean','definition of trimmed mean'),1,TRUE)
a<-table.element(a,hyperlink('unbiased1.htm','unbiased SD','definition of unbiased SD'),1,TRUE)
a<-table.row.end(a)
for (i in 1:length(y[,1]))
{
a<-table.row.start(a)
a<-table.element(a,dimnames(t(x))[[2]][i],1,TRUE)
a<-table.element(a,round(mean(z[i], trim=par3/100), digits=2))
a<-table.element(a,round(sd(z[i]), digits=2))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')