R version 2.13.0 (2011-04-13)
Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)

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You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

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Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> x <- c(362
+ ,361
+ ,361
+ ,356
+ ,364
+ ,375
+ ,391
+ ,379
+ ,389
+ ,387
+ ,379
+ ,385
+ ,399
+ ,388
+ ,392
+ ,395
+ ,395
+ ,370
+ ,376
+ ,367
+ ,356
+ ,362
+ ,346
+ ,347
+ ,350
+ ,361
+ ,358
+ ,334
+ ,331
+ ,337
+ ,337
+ ,341
+ ,344
+ ,342
+ ,353
+ ,355
+ ,354
+ ,353
+ ,365
+ ,366
+ ,354
+ ,353
+ ,363
+ ,368
+ ,366
+ ,376
+ ,383
+ ,382
+ ,386
+ ,389
+ ,388
+ ,382
+ ,379
+ ,374
+ ,380
+ ,383
+ ,384
+ ,385
+ ,378
+ ,378
+ ,378
+ ,383
+ ,381
+ ,382
+ ,382
+ ,390
+ ,401
+ ,392
+ ,401
+ ,406
+ ,408
+ ,421
+ ,412
+ ,407
+ ,411
+ ,405
+ ,416
+ ,410
+ ,397
+ ,409
+ ,406
+ ,406
+ ,412
+ ,426
+ ,423
+ ,425
+ ,425
+ ,423
+ ,434
+ ,434
+ ,440
+ ,422
+ ,431
+ ,442
+ ,448
+ ,448
+ ,475
+ ,481
+ ,488
+ ,476
+ ,474
+ ,455
+ ,455
+ ,434
+ ,447
+ ,455
+ ,459
+ ,465
+ ,464
+ ,468
+ ,467
+ ,468
+ ,467
+ ,454
+ ,470
+ ,477
+ ,462
+ ,467
+ ,469
+ ,467
+ ,469
+ ,466
+ ,469
+ ,482
+ ,474
+ ,477
+ ,468
+ ,469
+ ,480
+ ,474
+ ,474
+ ,471
+ ,443
+ ,441
+ ,440
+ ,436
+ ,442
+ ,437
+ ,444
+ ,440
+ ,444
+ ,440
+ ,438
+ ,427
+ ,421
+ ,424
+ ,422
+ ,436
+ ,435
+ ,433
+ ,420
+ ,417
+ ,411
+ ,430
+ ,428
+ ,428
+ ,426
+ ,432
+ ,426
+ ,426
+ ,424
+ ,424
+ ,431
+ ,441
+ ,444
+ ,447
+ ,440
+ ,442
+ ,439
+ ,439
+ ,453
+ ,459
+ ,462
+ ,466
+ ,464
+ ,473
+ ,469
+ ,474
+ ,480
+ ,482
+ ,486
+ ,486
+ ,484
+ ,484
+ ,487
+ ,490
+ ,491
+ ,495
+ ,497
+ ,496
+ ,489
+ ,485
+ ,490
+ ,493
+ ,487
+ ,495
+ ,506
+ ,492
+ ,500
+ ,499
+ ,518
+ ,517
+ ,505
+ ,522
+ ,519
+ ,519
+ ,522
+ ,519
+ ,543
+ ,537
+ ,537
+ ,520
+ ,523
+ ,526
+ ,537
+ ,534
+ ,536
+ ,557
+ ,554
+ ,550
+ ,549
+ ,575
+ ,595
+ ,636
+ ,628
+ ,594
+ ,590
+ ,590
+ ,605
+ ,618
+ ,630
+ ,638
+ ,645
+ ,640
+ ,640
+ ,634
+ ,647
+ ,682
+ ,679
+ ,677
+ ,697
+ ,702
+ ,679
+ ,685
+ ,695
+ ,685
+ ,688
+ ,685
+ ,694
+ ,694
+ ,697
+ ,700
+ ,695
+ ,693
+ ,693
+ ,722
+ ,725
+ ,715)
> ylimmax = ''
> ylimmin = ''
> main = 'Robustness of Central Tendency'
> 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] 466.5543
> sqrtn <- sqrt(length(x))
> (armse <- sd(x) / sqrtn)
[1] 5.94732
> (armose <- arm / armse)
[1] 78.44782
> (geo <- geomean(x))
[1] 457.7961
> (har <- harmean(x))
[1] 449.9333
> (qua <- quamean(x))
[1] 476.1965
> (win <- winmean(x))
          [,1]     [,2]
 [1,] 466.5543 5.944344
 [2,] 466.5233 5.933390
 [3,] 466.3721 5.909346
 [4,] 466.4031 5.899346
 [5,] 466.3643 5.888839
 [6,] 466.4109 5.885046
 [7,] 466.4109 5.872439
 [8,] 466.4419 5.869975
 [9,] 466.5116 5.856503
[10,] 466.6279 5.847606
[11,] 466.5853 5.841165
[12,] 466.5853 5.841165
[13,] 466.3837 5.799630
[14,] 466.2209 5.775530
[15,] 466.2791 5.771151
[16,] 466.3411 5.766516
[17,] 466.1434 5.737464
[18,] 466.0736 5.696561
[19,] 466.2946 5.680439
[20,] 466.1395 5.657903
[21,] 463.6977 5.316650
[22,] 463.6124 5.287436
[23,] 463.1667 5.228354
[24,] 463.2597 5.221377
[25,] 463.1628 5.188687
[26,] 463.0620 5.154842
[27,] 462.9574 5.119848
[28,] 462.5233 5.063698
[29,] 462.4109 5.026504
[30,] 461.3643 4.870568
[31,] 460.0426 4.660246
[32,] 459.2984 4.474921
[33,] 459.2984 4.450385
[34,] 458.9031 4.378929
[35,] 458.9031 4.378929
[36,] 457.0891 4.119609
[37,] 454.5078 3.841533
[38,] 454.0659 3.795964
[39,] 453.6124 3.722744
[40,] 453.4574 3.707161
[41,] 452.5039 3.612869
[42,] 451.6899 3.506093
[43,] 451.8566 3.492885
[44,] 452.0271 3.479477
[45,] 451.8527 3.462944
[46,] 451.4961 3.429395
[47,] 450.0388 3.295777
[48,] 449.6667 3.231161
[49,] 449.4767 3.214438
[50,] 449.4767 3.214438
[51,] 449.2791 3.164003
[52,] 449.2791 3.130363
[53,] 449.2791 3.130363
[54,] 449.4884 3.113698
[55,] 449.4884 3.078333
[56,] 449.4884 3.042457
[57,] 447.0581 2.839151
[58,] 447.0581 2.802872
[59,] 445.9147 2.712504
[60,] 445.9147 2.675556
[61,] 445.6783 2.620067
[62,] 445.6783 2.582323
[63,] 445.4341 2.563881
[64,] 446.1783 2.504109
[65,] 445.6744 2.466182
[66,] 445.9302 2.406408
[67,] 446.1899 2.346213
[68,] 446.4535 2.285625
[69,] 446.4535 2.285625
[70,] 447.2674 2.182572
[71,] 447.2674 2.141464
[72,] 446.9884 2.120894
[73,] 446.9884 2.120894
[74,] 446.9884 2.078370
[75,] 447.2791 2.056687
[76,] 447.2791 2.013318
[77,] 447.2791 1.969583
[78,] 447.5814 1.947400
[79,] 446.9690 1.903185
[80,] 447.2791 1.880465
[81,] 446.9651 1.857998
[82,] 447.9186 1.743426
[83,] 448.2403 1.720602
[84,] 448.2403 1.582531
[85,] 448.5698 1.559763
[86,] 448.2364 1.536221
> (tri <- trimean(x))
          [,1]     [,2]
 [1,] 466.0742 5.883957
 [2,] 465.5866 5.820462
 [3,] 465.1071 5.759595
 [4,] 464.6720 5.704472
 [5,] 464.2218 5.649289
 [6,] 463.7724 5.593644
 [7,] 463.3074 5.535766
 [8,] 462.8347 5.476959
 [9,] 462.3500 5.415309
[10,] 461.8487 5.352137
[11,] 461.3263 5.286532
[12,] 460.7991 5.217987
[13,] 460.2629 5.145457
[14,] 459.7348 5.073350
[15,] 459.2105 4.999575
[16,] 458.6726 4.921755
[17,] 458.1205 4.839554
[18,] 457.5721 4.755063
[19,] 457.0182 4.669016
[20,] 456.4404 4.578689
[21,] 455.8611 4.484431
[22,] 455.4112 4.414610
[23,] 454.9575 4.342756
[24,] 454.5190 4.271228
[25,] 454.0673 4.195500
[26,] 453.6117 4.117315
[27,] 453.1520 4.036484
[28,] 452.6881 3.952794
[29,] 452.2350 3.867770
[30,] 451.7778 3.779528
[31,] 451.3571 3.697451
[32,] 450.9845 3.625912
[33,] 450.6354 3.563071
[34,] 450.2789 3.497504
[35,] 449.9309 3.432492
[36,] 449.5753 3.362699
[37,] 449.2826 3.306928
[38,] 449.0824 3.266713
[39,] 448.8944 3.226746
[40,] 448.7191 3.188755
[41,] 448.5455 3.149086
[42,] 448.4023 3.112799
[43,] 448.2849 3.080712
[44,] 448.1588 3.047042
[45,] 448.0238 3.011656
[46,] 447.8916 2.974690
[47,] 447.7683 2.937126
[48,] 447.6914 2.905369
[49,] 447.6250 2.875191
[50,] 447.5633 2.843700
[51,] 447.5000 2.809700
[52,] 447.4416 2.776192
[53,] 447.3816 2.742094
[54,] 447.3200 2.705175
[55,] 447.2500 2.666222
[56,] 447.1781 2.626321
[57,] 447.1042 2.585404
[58,] 447.1056 2.554778
[59,] 447.1071 2.523817
[60,] 447.1449 2.495941
[61,] 447.1838 2.467925
[62,] 447.2313 2.440929
[63,] 447.2803 2.413872
[64,] 447.3385 2.385395
[65,] 447.3750 2.358339
[66,] 447.4286 2.331113
[67,] 447.4758 2.305322
[68,] 447.5164 2.281094
[69,] 447.5500 2.258561
[70,] 447.5847 2.233550
[71,] 447.5948 2.213255
[72,] 447.6053 2.193540
[73,] 447.6250 2.172949
[74,] 447.6455 2.149872
[75,] 447.6667 2.127268
[76,] 447.6792 2.103586
[77,] 447.6923 2.080398
[78,] 447.7059 2.057775
[79,] 447.7100 2.034019
[80,] 447.7347 2.010783
[81,] 447.7500 1.986357
[82,] 447.7766 1.960497
[83,] 447.7717 1.941334
[84,] 447.7556 1.921253
[85,] 447.7386 1.910381
[86,] 447.7093 1.899303
> (midr <- midrange(x))
[1] 528
> midm <- array(NA,dim=8)
> for (j in 1:8) midm[j] <- midmean(x,j)
> midm
[1] 446.9690 447.7023 447.7023 447.7023 446.9690 447.7023 447.7023 447.7023
> postscript(file="/var/wessaorg/rcomp/tmp/1i8251324629106.ps",horizontal=F,onefile=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/wessaorg/rcomp/tmp/2f8fl1324629106.ps",horizontal=F,onefile=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/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/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/wessaorg/rcomp/tmp/387ux1324629106.tab") 
> 
> try(system("convert tmp/1i8251324629106.ps tmp/1i8251324629106.png",intern=TRUE))
character(0)
> try(system("convert tmp/2f8fl1324629106.ps tmp/2f8fl1324629106.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.527   0.196   1.793