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

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(unlist(z[i]), trim=par3/100, na.rm=TRUE), digits=2))
a<-table.element(a,round(sd(unlist(z[i]), na.rm=TRUE), digits=2))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')