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89	81	109	83	95	
90	91	88	102	92	
82	96	87	75	85	
82	85	78	92	83	
71	74	72	94	73	
80	78	85	88	81	
62	71	73	77	63	
77	72	77	63	77	
80	87	90	73	82	
87	72	78	85	82	
96	90	96	80	95	
80	87	84	77	85	
85	89	87	67	88	
89	110	105	98	98	
89	95	89	89	87	
73	72	78	63	71	
88	70	96	97	89	
86	79	79	77	86	
83	92	90	96	88	
91	93	96	84	93	
98	97	95	94	95	
80	75	79	70	78	
84	88	86	100	84	
90	105	99	88	97	
92	82	111	97	95	
86	89	105	78	88	
117	114	123	108	121	
88	81	102	81	97	
86	73	82	96	82	
78	82	86	84	82	
104	110	117	104	108	
89	93	94	87	90	
99	114	110	98	113	
84	91	86	89	86	
89	97	109	93	105	
95	97	118	89	105	
58	68	64	63	60	
77	72	78	84	75	
77	81	86	82	79	
98	102	98	105	104	
58	62	64	70	60	
81	102	84	94	87	
92	84	87	101	93	
94	75	88	83	85	
87	102	106	88	97	
75	62	78	69	67	
80	100	79	94	85	
84	82	95	82	86	
87	78	98	82	88	
114	106	101	109	114	
97	88	104	86	97	
102	85	91	99	93	
80	97	78	82	80	
112	114	123	114	118	
104	105	109	99	109	
75	100	77	91	81	
82	72	77	81	79	
92	106	102	102	104	
102	78	88	101	97	
73	80	81	72	75	
78	88	83	91	82	
74	62	72	83	71	
92	93	95	102	92	
97	87	109	103	104	
92	109	91	93	99	
91	91	87	88	89	
102	110	112	110	114	
89	98	95	100	95	
98	99	103	88	106	
117	95	108	119	117	
92	97	116	98	109	
70	88	71	90	74	
63	72	70	69	63	
91	102	105	98	103	
106	95	112	98	107	
81	93	86	81	86	
98	90	109	93	99	
88	80	112	91	87	
95	75	97	86	93	
105	109	122	95	114	
90	75	97	87	82	
58	72	64	63	60	
86	77	84	89	83	
112	93	110	108	111	
71	72	70	99	75	
98	91	100	90	94	
87	95	102	91	91	
98	111	108	82	100	
117	105	123	119	121	
98	90	78	97	90	
98	105	109	108	105	
90	90	106	101	97	
84	92	95	96	92	
86	95	108	97	92	
68	75	74	69	67	
86	92	86	89	90	
77	100	82	84	85	
83	82	88	79	85	
90	102	96	103	97	
107	104	114	92	118	
102	98	111	104	109	
90	95	88	102	94	
113	114	123	106	121	
86	93	89	93	85	
105	110	114	108	112	
110	104	121	119	118	
82	91	100	102	93	
89	79	83	83	85	
99	97	92	92	97	
113	102	108	119	121	
91	77	87	100	83	
92	105	84	97	89	
86	95	95	103	92	
91	104	90	95	89	
82	75	82	73	82	
86	82	84	86	85	
86	91	96	88	92	
102	105	109	102	112	
84	71	84	87	79	
80	89	83	100	84	
96	79	93	88	92	
117	113	120	100	118	
88	82	83	79	82	
99	102	103	90	100	
89	82	103	83	87	
86	92	102	95	97	
98	82	90	89	87	
58	86	69	64	70	
98	108	114	108	110	
58	74	64	80	60	
81	87	87	83	81	
90	97	116	96	94	
112	102	121	108	114	
84	75	90	86	85	
84	82	92	88	85	
75	72	81	97	79	
78	88	84	110	82	
94	97	106	102	102	
75	85	75	92	73	
82	62	79	91	78	
87	95	80	92	84	
59	95	74	72	70	
68	72	66	88	66	
80	92	81	99	79	
94	91	98	95	95	
87	97	99	83	95	
70	78	68	68	69	
113	95	100	101	109	
99	91	97	91	100	
90	95	99	89	91	
102	88	104	98	99	
80	92	82	89	84	
98	97	92	98	101	
98	104	99	97	99	
95	113	109	98	104	
104	113	106	113	109	
86	82	89	83	87	
84	90	87	92	88	
85	91	98	113	87	
90	95	95	103	95	
86	102	92	96	92	
97	92	90	94	100	

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')