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