R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> x <- c(85
+ ,105
+ ,108
+ ,92
+ ,112.5
+ ,112
+ ,104
+ ,69
+ ,94.5
+ ,68.5
+ ,104
+ ,103.5
+ ,123.5
+ ,93
+ ,50.5
+ ,89
+ ,107
+ ,78.5
+ ,115
+ ,114
+ ,85
+ ,81
+ ,83.5
+ ,112
+ ,101
+ ,103.5
+ ,93.5
+ ,112
+ ,140
+ ,83.5
+ ,90
+ ,84
+ ,110.5
+ ,96
+ ,95
+ ,121
+ ,99.5
+ ,142.5
+ ,118
+ ,104.5
+ ,102.5
+ ,89.5
+ ,95
+ ,98.5
+ ,94
+ ,108
+ ,63.5
+ ,84.5
+ ,93.5
+ ,112
+ ,148.5
+ ,112
+ ,109
+ ,91.5
+ ,75
+ ,84
+ ,107
+ ,92.5
+ ,109.5
+ ,84
+ ,102.5
+ ,106
+ ,77
+ ,111.5
+ ,114
+ ,75
+ ,73.5
+ ,93.5
+ ,105
+ ,113.5
+ ,140
+ ,77
+ ,84.5
+ ,113.5
+ ,77.5
+ ,117.5
+ ,98
+ ,112
+ ,101
+ ,95
+ ,81
+ ,91
+ ,142
+ ,98.5
+ ,112
+ ,116.5
+ ,98.5
+ ,83.5
+ ,133
+ ,91.5
+ ,72.5
+ ,106.5
+ ,67
+ ,122.5
+ ,74
+ ,144.5
+ ,84
+ ,72.5
+ ,64
+ ,116
+ ,84
+ ,93.5
+ ,111.5
+ ,92
+ ,115
+ ,85
+ ,108
+ ,108
+ ,85
+ ,86
+ ,110.5
+ ,98
+ ,105
+ ,76.5
+ ,84
+ ,128
+ ,87
+ ,128
+ ,111
+ ,79
+ ,90
+ ,84
+ ,112
+ ,93
+ ,117
+ ,84
+ ,99.5
+ ,95
+ ,84
+ ,134
+ ,171.5
+ ,98.5
+ ,118.5
+ ,94.5
+ ,105
+ ,104
+ ,83
+ ,105.5
+ ,84
+ ,86
+ ,81
+ ,94
+ ,78.5
+ ,119.5
+ ,133
+ ,119
+ ,95
+ ,112
+ ,75
+ ,92
+ ,112
+ ,98.5
+ ,112.5
+ ,112.5
+ ,108
+ ,108
+ ,88
+ ,106
+ ,92
+ ,117.5
+ ,84
+ ,112
+ ,100
+ ,112
+ ,84
+ ,127.5
+ ,80.5
+ ,93.5
+ ,86.5
+ ,92.5
+ ,108.5
+ ,121
+ ,112
+ ,114
+ ,84
+ ,81
+ ,111.5
+ ,81
+ ,70
+ ,140
+ ,117
+ ,84
+ ,112
+ ,150.5
+ ,147
+ ,105
+ ,119.5
+ ,84
+ ,91
+ ,101
+ ,117.5
+ ,121
+ ,133
+ ,112
+ ,91.5
+ ,105
+ ,111
+ ,112
+ ,114
+ ,91
+ ,98
+ ,118
+ ,115.5
+ ,112
+ ,112
+ ,91
+ ,85
+ ,112
+ ,87.5
+ ,118
+ ,83.5
+ ,116
+ ,89
+ ,171.5
+ ,112
+ ,72
+ ,150
+ ,134.5
+ ,97
+ ,71.5
+ ,73.5
+ ,112
+ ,75
+ ,128
+ ,98
+ ,84
+ ,99
+ ,112
+ ,79.5
+ ,80.5
+ ,102.5
+ ,76
+ ,112
+ ,114
+ ,140
+ ,107.5
+ ,87)
> ylimmax = ''
> ylimmin = ''
> main = 'Robustness of Central Tendency'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: Wessa, P., (2007), Central Tendency (v1.0.2) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_centraltendency.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> geomean <- function(x) {
+ return(exp(mean(log(x))))
+ }
> harmean <- function(x) {
+ return(1/mean(1/x))
+ }
> quamean <- function(x) {
+ return(sqrt(mean(x*x)))
+ }
> winmean <- function(x) {
+ x <-sort(x[!is.na(x)])
+ n<-length(x)
+ denom <- 3
+ nodenom <- n/denom
+ if (nodenom>40) denom <- n/40
+ sqrtn = sqrt(n)
+ roundnodenom = floor(nodenom)
+ win <- array(NA,dim=c(roundnodenom,2))
+ for (j in 1:roundnodenom) {
+ win[j,1] <- (j*x[j+1]+sum(x[(j+1):(n-j)])+j*x[n-j])/n
+ win[j,2] <- sd(c(rep(x[j+1],j),x[(j+1):(n-j)],rep(x[n-j],j)))/sqrtn
+ }
+ return(win)
+ }
> trimean <- function(x) {
+ x <-sort(x[!is.na(x)])
+ n<-length(x)
+ denom <- 3
+ nodenom <- n/denom
+ if (nodenom>40) denom <- n/40
+ sqrtn = sqrt(n)
+ roundnodenom = floor(nodenom)
+ tri <- array(NA,dim=c(roundnodenom,2))
+ for (j in 1:roundnodenom) {
+ tri[j,1] <- mean(x,trim=j/n)
+ tri[j,2] <- sd(x[(j+1):(n-j)]) / sqrt(n-j*2)
+ }
+ return(tri)
+ }
> midrange <- function(x) {
+ return((max(x)+min(x))/2)
+ }
> q1 <- function(data,n,p,i,f) {
+ np <- n*p;
+ i <<- floor(np)
+ f <<- np - i
+ qvalue <- (1-f)*data[i] + f*data[i+1]
+ }
> q2 <- function(data,n,p,i,f) {
+ np <- (n+1)*p
+ i <<- floor(np)
+ f <<- np - i
+ qvalue <- (1-f)*data[i] + f*data[i+1]
+ }
> q3 <- function(data,n,p,i,f) {
+ np <- n*p
+ i <<- floor(np)
+ f <<- np - i
+ if (f==0) {
+ qvalue <- data[i]
+ } else {
+ qvalue <- data[i+1]
+ }
+ }
> q4 <- function(data,n,p,i,f) {
+ np <- n*p
+ i <<- floor(np)
+ f <<- np - i
+ if (f==0) {
+ qvalue <- (data[i]+data[i+1])/2
+ } else {
+ qvalue <- data[i+1]
+ }
+ }
> q5 <- function(data,n,p,i,f) {
+ np <- (n-1)*p
+ i <<- floor(np)
+ f <<- np - i
+ if (f==0) {
+ qvalue <- data[i+1]
+ } else {
+ qvalue <- data[i+1] + f*(data[i+2]-data[i+1])
+ }
+ }
> q6 <- function(data,n,p,i,f) {
+ np <- n*p+0.5
+ i <<- floor(np)
+ f <<- np - i
+ qvalue <- data[i]
+ }
> q7 <- function(data,n,p,i,f) {
+ np <- (n+1)*p
+ i <<- floor(np)
+ f <<- np - i
+ if (f==0) {
+ qvalue <- data[i]
+ } else {
+ qvalue <- f*data[i] + (1-f)*data[i+1]
+ }
+ }
> q8 <- function(data,n,p,i,f) {
+ np <- (n+1)*p
+ i <<- floor(np)
+ f <<- np - i
+ if (f==0) {
+ qvalue <- data[i]
+ } else {
+ if (f == 0.5) {
+ qvalue <- (data[i]+data[i+1])/2
+ } else {
+ if (f < 0.5) {
+ qvalue <- data[i]
+ } else {
+ qvalue <- data[i+1]
+ }
+ }
+ }
+ }
> midmean <- function(x,def) {
+ x <-sort(x[!is.na(x)])
+ n<-length(x)
+ if (def==1) {
+ qvalue1 <- q1(x,n,0.25,i,f)
+ qvalue3 <- q1(x,n,0.75,i,f)
+ }
+ if (def==2) {
+ qvalue1 <- q2(x,n,0.25,i,f)
+ qvalue3 <- q2(x,n,0.75,i,f)
+ }
+ if (def==3) {
+ qvalue1 <- q3(x,n,0.25,i,f)
+ qvalue3 <- q3(x,n,0.75,i,f)
+ }
+ if (def==4) {
+ qvalue1 <- q4(x,n,0.25,i,f)
+ qvalue3 <- q4(x,n,0.75,i,f)
+ }
+ if (def==5) {
+ qvalue1 <- q5(x,n,0.25,i,f)
+ qvalue3 <- q5(x,n,0.75,i,f)
+ }
+ if (def==6) {
+ qvalue1 <- q6(x,n,0.25,i,f)
+ qvalue3 <- q6(x,n,0.75,i,f)
+ }
+ if (def==7) {
+ qvalue1 <- q7(x,n,0.25,i,f)
+ qvalue3 <- q7(x,n,0.75,i,f)
+ }
+ if (def==8) {
+ qvalue1 <- q8(x,n,0.25,i,f)
+ qvalue3 <- q8(x,n,0.75,i,f)
+ }
+ midm <- 0
+ myn <- 0
+ roundno4 <- round(n/4)
+ round3no4 <- round(3*n/4)
+ for (i in 1:n) {
+ if ((x[i]>=qvalue1) & (x[i]<=qvalue3)){
+ midm = midm + x[i]
+ myn = myn + 1
+ }
+ }
+ midm = midm / myn
+ return(midm)
+ }
> (arm <- mean(x))
[1] 101.3080
> sqrtn <- sqrt(length(x))
> (armse <- sd(x) / sqrtn)
[1] 1.262809
> (armose <- arm / armse)
[1] 80.22434
> (geo <- geomean(x))
[1] 99.49517
> (har <- harmean(x))
[1] 97.70293
> (qua <- quamean(x))
[1] 103.1487
> (win <- winmean(x))
           [,1]      [,2]
 [1,] 101.36287 1.2546224
 [2,] 101.18987 1.2178018
 [3,] 101.22152 1.2119900
 [4,] 101.22152 1.2047548
 [5,] 101.20042 1.1983536
 [6,] 101.16245 1.1854743
 [7,] 101.14768 1.1716379
 [8,] 101.14768 1.1673267
 [9,] 101.09072 1.1542692
[10,] 101.09072 1.1542692
[11,] 101.13713 1.1494691
[12,] 101.13713 1.1494691
[13,] 100.86287 1.1055615
[14,] 100.89241 1.0957683
[15,] 100.82911 1.0877507
[16,] 100.82911 1.0877507
[17,] 100.82911 1.0877507
[18,] 100.52532 1.0349015
[19,] 100.56540 1.0309064
[20,] 100.60759 1.0267641
[21,] 100.56329 1.0217854
[22,] 100.23840 0.9777323
[23,] 100.23840 0.9586194
[24,] 100.08650 0.9440138
[25,] 100.13924 0.9389427
[26,] 100.19409 0.9337507
[27,] 100.13713 0.9073783
[28,] 100.13713 0.9073783
[29,] 100.13713 0.8963111
[30,] 100.07384 0.8907151
[31,] 100.00844 0.8850317
[32,] 100.00844 0.8850317
[33,] 100.00844 0.8850317
[34,] 100.22363 0.8535293
[35,] 100.29747 0.8472708
[36,] 100.29747 0.8472708
[37,] 100.21941 0.8406114
[38,] 100.21941 0.8406114
[39,] 100.21941 0.8268116
[40,] 100.13502 0.8198310
[41,] 100.13502 0.8198310
[42,] 100.04641 0.8126279
[43,]  99.95570 0.8053825
[44,]  99.95570 0.8053825
[45,]  99.76582 0.7906232
[46,]  99.76582 0.7906232
[47,]  99.76582 0.7906232
[48,]  99.76582 0.7906232
[49,]  99.76582 0.7906232
[50,]  99.66034 0.7826473
[51,]  99.66034 0.7826473
[52,]  99.44093 0.7665044
[53,]  99.44093 0.7665044
[54,]  99.44093 0.7665044
[55,]  99.44093 0.7483285
[56,]  99.44093 0.7483285
[57,]  99.56118 0.7382160
[58,]  99.56118 0.7382160
[59,]  99.56118 0.7382160
[60,]  99.56118 0.7382160
[61,]  99.56118 0.7382160
[62,]  99.82278 0.7165888
[63,]  99.82278 0.7165888
[64,]  99.95781 0.7056144
[65,] 100.09494 0.6945955
[66,] 100.09494 0.6945955
[67,] 100.23629 0.6833678
[68,] 100.37975 0.6721041
[69,] 100.67089 0.6496569
[70,] 100.67089 0.6496569
[71,] 100.82068 0.6383270
[72,] 100.97257 0.6269869
[73,] 100.97257 0.6269869
[74,] 101.28481 0.6041426
[75,] 101.28481 0.6041426
[76,] 101.28481 0.6041426
[77,] 101.28481 0.6041426
[78,] 101.28481 0.5800000
[79,] 101.28481 0.5800000
> (tri <- trimean(x))
          [,1]      [,2]
 [1,] 101.3080 1.2187841
 [2,] 101.2255 1.1803935
 [3,] 101.0325 1.1600672
 [4,] 101.0325 1.1407414
 [5,] 100.9009 1.1223930
 [6,] 100.8378 1.1045076
 [7,] 100.7803 1.0882256
 [8,] 100.7803 1.0734843
 [9,] 100.6667 1.0585739
[10,] 100.6152 1.0447164
[11,] 100.5628 1.0300358
[12,] 100.5047 1.0150671
[13,] 100.4455 0.9991773
[14,] 100.4091 0.9873344
[15,] 100.3696 0.9758045
[16,] 100.3696 0.9643931
[17,] 100.2980 0.9522794
[18,] 100.2612 0.9394086
[19,] 100.2437 0.9305339
[20,] 100.2234 0.9214413
[21,] 100.2000 0.9121134
[22,] 100.1788 0.9026008
[23,] 100.1754 0.8959490
[24,] 100.1720 0.8902808
[25,] 100.1765 0.8852768
[26,] 100.1784 0.8802760
[27,] 100.1776 0.8752757
[28,] 100.1796 0.8716850
[29,] 100.1816 0.8678057
[30,] 100.1836 0.8643332
[31,] 100.1886 0.8609247
[32,] 100.1886 0.8575793
[33,] 100.2047 0.8539420
[34,] 100.2130 0.8499919
[35,] 100.2126 0.8476320
[36,] 100.2091 0.8453939
[37,] 100.2055 0.8429094
[38,] 100.2050 0.8405539
[39,] 100.2044 0.8379367
[40,] 100.2038 0.8358441
[41,] 100.2065 0.8338988
[42,] 100.2092 0.8317014
[43,] 100.2152 0.8296454
[44,] 100.2248 0.8277321
[45,] 100.2347 0.8255527
[46,] 100.2517 0.8239141
[47,] 100.2692 0.8220133
[48,] 100.2872 0.8198283
[49,] 100.3058 0.8173343
[50,] 100.3248 0.8145045
[51,] 100.3481 0.8117652
[52,] 100.3722 0.8086570
[53,] 100.4046 0.8060640
[54,] 100.4380 0.8030912
[55,] 100.4724 0.7997021
[56,] 100.5080 0.7969900
[57,] 100.5447 0.7938607
[58,] 100.5785 0.7909615
[59,] 100.6134 0.7876123
[60,] 100.6496 0.7837660
[61,] 100.6870 0.7793693
[62,] 100.7257 0.7743618
[63,] 100.7257 0.7702990
[64,] 100.7568 0.7656315
[65,] 100.8178 0.7611336
[66,] 100.8429 0.7568162
[67,] 100.8689 0.7518288
[68,] 100.8911 0.7469941
[69,] 100.9091 0.7423201
[70,] 100.9175 0.7386992
[71,] 100.9263 0.7344113
[72,] 100.9301 0.7303044
[73,] 100.9286 0.7263811
[74,] 100.9270 0.7216974
[75,] 100.9138 0.7180887
[76,] 100.9000 0.7137014
[77,] 100.8855 0.7084211
[78,] 100.8704 0.7021120
[79,] 100.8544 0.6970024
> (midr <- midrange(x))
[1] 111
> midm <- array(NA,dim=8)
> for (j in 1:8) midm[j] <- midmean(x,j)
> midm
[1] 100.728 100.728 100.728 100.728 100.728 100.728 100.728 100.728
> postscript(file="/var/www/html/rcomp/tmp/1ehy01289122375.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> lb <- win[,1] - 2*win[,2]
> ub <- win[,1] + 2*win[,2]
> if ((ylimmin == '') | (ylimmax == '')) plot(win[,1],type='b',main=main, xlab='j', pch=19, ylab='Winsorized Mean(j/n)', ylim=c(min(lb),max(ub))) else plot(win[,1],type='l',main=main, xlab='j', pch=19, ylab='Winsorized Mean(j/n)', ylim=c(ylimmin,ylimmax))
> lines(ub,lty=3)
> lines(lb,lty=3)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/278fl1289122375.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> lb <- tri[,1] - 2*tri[,2]
> ub <- tri[,1] + 2*tri[,2]
> if ((ylimmin == '') | (ylimmax == '')) plot(tri[,1],type='b',main=main, xlab='j', pch=19, ylab='Trimmed Mean(j/n)', ylim=c(min(lb),max(ub))) else plot(tri[,1],type='l',main=main, xlab='j', pch=19, ylab='Trimmed Mean(j/n)', ylim=c(ylimmin,ylimmax))
> lines(ub,lty=3)
> lines(lb,lty=3)
> grid()
> dev.off()
null device 
          1 
> 
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
> 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Central Tendency - Ungrouped Data',4,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Measure',header=TRUE)
> a<-table.element(a,'Value',header=TRUE)
> a<-table.element(a,'S.E.',header=TRUE)
> a<-table.element(a,'Value/S.E.',header=TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/arithmetic_mean.htm', 'Arithmetic Mean', 'click to view the definition of the Arithmetic Mean'),header=TRUE)
> a<-table.element(a,arm)
> a<-table.element(a,hyperlink('http://www.xycoon.com/arithmetic_mean_standard_error.htm', armse, 'click to view the definition of the Standard Error of the Arithmetic Mean'))
> a<-table.element(a,armose)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/geometric_mean.htm', 'Geometric Mean', 'click to view the definition of the Geometric Mean'),header=TRUE)
> a<-table.element(a,geo)
> a<-table.element(a,'')
> a<-table.element(a,'')
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/harmonic_mean.htm', 'Harmonic Mean', 'click to view the definition of the Harmonic Mean'),header=TRUE)
> a<-table.element(a,har)
> a<-table.element(a,'')
> a<-table.element(a,'')
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/quadratic_mean.htm', 'Quadratic Mean', 'click to view the definition of the Quadratic Mean'),header=TRUE)
> a<-table.element(a,qua)
> a<-table.element(a,'')
> a<-table.element(a,'')
> a<-table.row.end(a)
> for (j in 1:length(win[,1])) {
+ a<-table.row.start(a)
+ mylabel <- paste('Winsorized Mean (',j)
+ mylabel <- paste(mylabel,'/')
+ mylabel <- paste(mylabel,length(win[,1]))
+ mylabel <- paste(mylabel,')')
+ a<-table.element(a,hyperlink('http://www.xycoon.com/winsorized_mean.htm', mylabel, 'click to view the definition of the Winsorized Mean'),header=TRUE)
+ a<-table.element(a,win[j,1])
+ a<-table.element(a,win[j,2])
+ a<-table.element(a,win[j,1]/win[j,2])
+ a<-table.row.end(a)
+ }
> for (j in 1:length(tri[,1])) {
+ a<-table.row.start(a)
+ mylabel <- paste('Trimmed Mean (',j)
+ mylabel <- paste(mylabel,'/')
+ mylabel <- paste(mylabel,length(tri[,1]))
+ mylabel <- paste(mylabel,')')
+ a<-table.element(a,hyperlink('http://www.xycoon.com/arithmetic_mean.htm', mylabel, 'click to view the definition of the Trimmed Mean'),header=TRUE)
+ a<-table.element(a,tri[j,1])
+ a<-table.element(a,tri[j,2])
+ a<-table.element(a,tri[j,1]/tri[j,2])
+ a<-table.row.end(a)
+ }
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/median_1.htm', 'Median', 'click to view the definition of the Median'),header=TRUE)
> a<-table.element(a,median(x))
> a<-table.element(a,'')
> a<-table.element(a,'')
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/midrange.htm', 'Midrange', 'click to view the definition of the Midrange'),header=TRUE)
> a<-table.element(a,midr)
> a<-table.element(a,'')
> a<-table.element(a,'')
> a<-table.row.end(a)
> a<-table.row.start(a)
> mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
> mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_1.htm','Weighted Average at Xnp',''),sep=' - ')
> a<-table.element(a,mylabel,header=TRUE)
> a<-table.element(a,midm[1])
> a<-table.element(a,'')
> a<-table.element(a,'')
> a<-table.row.end(a)
> a<-table.row.start(a)
> mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
> mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_2.htm','Weighted Average at X(n+1)p',''),sep=' - ')
> a<-table.element(a,mylabel,header=TRUE)
> a<-table.element(a,midm[2])
> a<-table.element(a,'')
> a<-table.element(a,'')
> a<-table.row.end(a)
> a<-table.row.start(a)
> mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
> mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_3.htm','Empirical Distribution Function',''),sep=' - ')
> a<-table.element(a,mylabel,header=TRUE)
> a<-table.element(a,midm[3])
> a<-table.element(a,'')
> a<-table.element(a,'')
> a<-table.row.end(a)
> a<-table.row.start(a)
> mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
> mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_4.htm','Empirical Distribution Function - Averaging',''),sep=' - ')
> a<-table.element(a,mylabel,header=TRUE)
> a<-table.element(a,midm[4])
> a<-table.element(a,'')
> a<-table.element(a,'')
> a<-table.row.end(a)
> a<-table.row.start(a)
> mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
> mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_5.htm','Empirical Distribution Function - Interpolation',''),sep=' - ')
> a<-table.element(a,mylabel,header=TRUE)
> a<-table.element(a,midm[5])
> a<-table.element(a,'')
> a<-table.element(a,'')
> a<-table.row.end(a)
> a<-table.row.start(a)
> mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
> mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_6.htm','Closest Observation',''),sep=' - ')
> a<-table.element(a,mylabel,header=TRUE)
> a<-table.element(a,midm[6])
> a<-table.element(a,'')
> a<-table.element(a,'')
> a<-table.row.end(a)
> a<-table.row.start(a)
> mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
> mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_7.htm','True Basic - Statistics Graphics Toolkit',''),sep=' - ')
> a<-table.element(a,mylabel,header=TRUE)
> a<-table.element(a,midm[7])
> a<-table.element(a,'')
> a<-table.element(a,'')
> a<-table.row.end(a)
> a<-table.row.start(a)
> mymid <- hyperlink('http://www.xycoon.com/midmean.htm', 'Midmean', 'click to view the definition of the Midmean')
> mylabel <- paste(mymid,hyperlink('http://www.xycoon.com/method_8.htm','MS Excel (old versions)',''),sep=' - ')
> a<-table.element(a,mylabel,header=TRUE)
> a<-table.element(a,midm[8])
> a<-table.element(a,'')
> a<-table.element(a,'')
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Number of observations',header=TRUE)
> a<-table.element(a,length(x))
> a<-table.element(a,'')
> a<-table.element(a,'')
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/3rb621289122375.tab") 
> 
> try(system("convert tmp/1ehy01289122375.ps tmp/1ehy01289122375.png",intern=TRUE))
character(0)
> try(system("convert tmp/278fl1289122375.ps tmp/278fl1289122375.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.201   0.405  10.180