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

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
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(9.913463687
+ ,9.913463687
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> 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: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.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] 0.1716304
> sqrtn <- sqrt(length(x))
> (armse <- sd(x) / sqrtn)
[1] 0.993561
> (armose <- arm / armse)
[1] 0.1727426
> (geo <- geomean(x))
[1] NaN
Warning message:
In log(x) : NaNs produced
> (har <- harmean(x))
[1] 18.93143
> (qua <- quamean(x))
[1] 18.82608
> (win <- winmean(x))
              [,1]      [,2]
  [1,]  0.17501924 0.9931945
  [2,]  0.09624147 0.9730424
  [3,]  0.01382480 0.9550449
  [4,] -0.14784187 0.9246096
  [5,] -0.23909187 0.9097259
  [6,] -0.25809187 0.9059895
  [7,] -0.32400853 0.8962834
  [8,] -0.38911964 0.8856167
  [9,] -0.38611964 0.8841198
 [10,] -0.44417520 0.8763012
 [11,] -0.50345298 0.8687390
 [12,] -0.53245298 0.8633599
 [13,] -0.54148076 0.8621811
 [14,] -0.56053631 0.8580337
 [15,] -0.58720298 0.8538046
 [16,] -0.61964742 0.8495536
 [17,] -0.60878631 0.8477974
 [18,] -0.68878631 0.8387364
 [19,] -0.69564742 0.8362721
 [20,] -0.72453631 0.8323423
 [21,] -0.72278631 0.8317299
 [22,] -0.77473076 0.8245168
 [23,] -0.78559187 0.8166565
 [24,] -0.79692520 0.8155513
 [25,] -0.81706409 0.8130775
 [26,] -0.83728631 0.8111319
 [27,] -0.91378631 0.7976686
 [28,] -0.94489742 0.7939494
 [29,] -0.94006409 0.7888246
 [30,] -0.87423076 0.7826509
 [31,] -0.86217520 0.7765079
 [32,] -0.94128631 0.7572505
 [33,] -0.96695298 0.7548577
 [34,] -0.95089742 0.7516784
 [35,] -0.99464742 0.7467466
 [36,] -0.99964742 0.7461487
 [37,] -1.09728631 0.7372392
 [38,] -1.09623076 0.7328659
 [39,] -1.14931409 0.7252541
 [40,] -1.20264742 0.7193056
 [41,] -1.20720298 0.7102948
 [42,] -1.24686964 0.6992059
 [43,] -1.22656409 0.6945859
 [44,] -1.27667520 0.6878173
 [45,] -1.27667520 0.6816347
 [46,] -1.27028631 0.6804896
 [47,] -1.25723076 0.6789825
 [48,] -1.27989742 0.6755993
 [49,] -1.33978631 0.6705295
 [50,] -1.37867520 0.6663864
 [51,] -1.35884187 0.6616300
 [52,] -1.28517520 0.6544036
 [53,] -1.23806409 0.6496336
 [54,] -1.34456409 0.6269194
 [55,] -1.36136964 0.6257481
 [56,] -1.30536964 0.6191231
 [57,] -1.27845298 0.6162567
 [58,] -1.25750853 0.6145869
 [59,] -1.25914742 0.6134938
 [60,] -1.37414742 0.6043436
 [61,] -1.35550853 0.6021043
 [62,] -1.36584187 0.5968388
 [63,] -1.34659187 0.5950530
 [64,] -1.35548076 0.5921083
 [65,] -1.14964742 0.5757730
 [66,] -1.18081409 0.5699491
 [67,] -1.14731409 0.5668446
 [68,] -1.17186964 0.5576091
 [69,] -1.08561964 0.5510766
 [70,] -1.02145298 0.5426869
 [71,] -1.03525853 0.5417616
 [72,] -1.04725853 0.5403941
 [73,] -1.01886964 0.5288762
 [74,] -1.12164742 0.5212658
 [75,] -1.08623076 0.5186460
 [76,] -0.96167520 0.5077806
 [77,] -0.94670298 0.5011025
 [78,] -0.70403631 0.4800849
 [79,] -0.73036964 0.4783521
 [80,] -0.72370298 0.4754893
 [81,] -0.63595298 0.4691437
 [82,] -0.66784187 0.4643053
 [83,] -0.56178631 0.4537405
 [84,] -0.56178631 0.4506488
 [85,] -0.55942520 0.4495537
 [86,] -0.51164742 0.4441644
 [87,] -0.50439742 0.4436839
 [88,] -0.48484187 0.4362947
 [89,] -0.47495298 0.4349978
 [90,] -0.41995298 0.4284684
 [91,] -0.36939742 0.4248666
 [92,] -0.35917520 0.4225500
 [93,] -0.35400854 0.4188726
 [94,] -0.35923076 0.4161704
 [95,] -0.42520298 0.4105373
 [96,] -0.39853631 0.4074584
 [97,] -0.44164742 0.4046864
 [98,] -0.46070298 0.3982452
 [99,] -0.50195298 0.3882802
[100,] -0.41028631 0.3800176
[101,] -0.48323076 0.3750707
[102,] -0.47473076 0.3738228
[103,] -0.48331409 0.3725668
[104,] -0.46309187 0.3705703
[105,] -0.46309187 0.3691082
[106,] -0.43953631 0.3643185
[107,] -0.46628631 0.3622786
[108,] -0.53828631 0.3544558
[109,] -0.42323076 0.3465494
[110,] -0.43850854 0.3418301
[111,] -0.42309187 0.3386004
[112,] -0.41375854 0.3342007
[113,] -0.39178631 0.3297756
[114,] -0.43295298 0.3260857
[115,] -0.44892520 0.3243278
[116,] -0.43603631 0.3200006
[117,] -0.52378631 0.3134862
[118,] -0.51067520 0.3122867
[119,] -0.54373076 0.3082878
[120,] -0.58039742 0.3056828
> (tri <- trimean(x))
                [,1]      [,2]
  [1,]  1.324022e-09 0.9591192
  [2,] -1.769857e-01 0.9228459
  [3,] -3.159148e-01 0.8956495
  [4,] -4.283261e-01 0.8738505
  [5,] -5.004506e-01 0.8598082
  [6,] -5.545248e-01 0.8486263
  [7,] -6.059294e-01 0.8377254
  [8,] -6.480770e-01 0.8280490
  [9,] -6.821503e-01 0.8196087
 [10,] -7.169775e-01 0.8110474
 [11,] -7.460334e-01 0.8031345
 [12,] -7.696613e-01 0.7957905
 [13,] -7.696613e-01 0.7887421
 [14,] -8.117773e-01 0.7815444
 [15,] -8.313545e-01 0.7744641
 [16,] -8.492192e-01 0.7674925
 [17,] -8.650639e-01 0.7606169
 [18,] -8.818141e-01 0.7536176
 [19,] -8.938034e-01 0.7470603
 [20,] -9.055363e-01 0.7404334
 [21,] -9.157816e-01 0.7338340
 [22,] -9.262515e-01 0.7270170
 [23,] -9.341478e-01 0.7204255
 [24,] -9.416004e-01 0.7140938
 [25,] -9.486008e-01 0.7075802
 [26,] -9.486008e-01 0.7009604
 [27,] -9.600657e-01 0.6941917
 [28,] -9.620955e-01 0.6879635
 [29,] -9.628277e-01 0.6816998
 [30,] -9.637696e-01 0.6754749
 [31,] -9.673752e-01 0.6693424
 [32,] -9.715025e-01 0.6632973
 [33,] -9.726588e-01 0.6580513
 [34,] -9.728719e-01 0.6527130
 [35,] -9.736742e-01 0.6473166
 [36,] -9.729252e-01 0.6419474
 [37,] -9.719909e-01 0.6363785
 [38,] -9.676983e-01 0.6310218
 [39,] -9.633803e-01 0.6256524
 [40,] -9.572506e-01 0.6204251
 [41,] -9.493061e-01 0.6152576
 [42,] -9.411015e-01 0.6102984
 [43,] -9.315363e-01 0.6056462
 [44,] -9.224554e-01 0.6010042
 [45,] -9.117215e-01 0.5964657
 [46,] -9.008274e-01 0.5920069
 [47,] -8.899574e-01 0.5873961
 [48,] -8.793015e-01 0.5826417
 [49,] -8.793015e-01 0.5778190
 [50,] -8.544979e-01 0.5729967
 [51,] -8.398696e-01 0.5681305
 [52,] -8.398696e-01 0.5632498
 [53,] -8.130324e-01 0.5584690
 [54,] -8.015760e-01 0.5536756
 [55,] -7.870963e-01 0.5496510
 [56,] -7.719395e-01 0.5454761
 [57,] -7.579997e-01 0.5413900
 [58,] -7.445281e-01 0.5372266
 [59,] -7.313710e-01 0.5329272
 [60,] -7.179530e-01 0.5284558
 [61,] -7.014103e-01 0.5241447
 [62,] -6.850533e-01 0.5197098
 [63,] -6.850533e-01 0.5152735
 [64,] -6.514501e-01 0.5106833
 [65,] -6.342320e-01 0.5059774
 [66,] -6.217118e-01 0.5017744
 [67,] -6.082177e-01 0.4975968
 [68,] -5.952863e-01 0.4933315
 [69,] -5.815363e-01 0.4892374
 [70,] -5.695818e-01 0.4852144
 [71,] -5.589216e-01 0.4813432
 [72,] -5.477400e-01 0.4772904
 [73,] -5.360690e-01 0.4730644
 [74,] -5.248382e-01 0.4691157
 [75,] -5.110125e-01 0.4652630
 [76,] -4.977382e-01 0.4613040
 [77,] -4.870703e-01 0.4576144
 [78,] -4.765363e-01 0.4540034
 [79,] -4.713383e-01 0.4511260
 [80,] -4.654363e-01 0.4481409
 [81,] -4.595666e-01 0.4450933
 [82,] -4.555669e-01 0.4421383
 [83,] -4.507631e-01 0.4392058
 [84,] -4.482551e-01 0.4365566
 [85,] -4.456942e-01 0.4338663
 [86,] -4.431321e-01 0.4310419
 [87,] -4.415901e-01 0.4282709
 [88,] -4.401776e-01 0.4253294
 [89,] -4.391737e-01 0.4225265
 [90,] -4.383696e-01 0.4195852
 [91,] -4.387835e-01 0.4167426
 [92,] -4.403431e-01 0.4138640
 [93,] -4.421685e-01 0.4108853
 [94,] -4.441526e-01 0.4078655
 [95,] -4.460657e-01 0.4047536
 [96,] -4.465363e-01 0.4016896
 [97,] -4.476207e-01 0.3985462
 [98,] -4.476207e-01 0.3953024
 [99,] -4.474622e-01 0.3921395
[100,] -4.462238e-01 0.3892425
[101,] -4.470426e-01 0.3865381
[102,] -4.462158e-01 0.3838653
[103,] -4.455623e-01 0.3810316
[104,] -4.455623e-01 0.3780240
[105,] -4.442696e-01 0.3748692
[106,] -4.438336e-01 0.3715247
[107,] -4.439336e-01 0.3681649
[108,] -4.434113e-01 0.3646284
[109,] -4.434113e-01 0.3612400
[110,] -4.416077e-01 0.3580186
[111,] -4.416812e-01 0.3547833
[112,] -4.421245e-01 0.3514418
[113,] -4.428050e-01 0.3480576
[114,] -4.440363e-01 0.3446282
[115,] -4.440363e-01 0.3411034
[116,] -4.441926e-01 0.3373458
[117,] -4.443935e-01 0.3335074
[118,] -4.424234e-01 0.3297300
[119,] -4.407166e-01 0.3256471
[120,] -4.381196e-01 0.3214283
> (midr <- midrange(x))
[1] 30.89346
> midm <- array(NA,dim=8)
> for (j in 1:8) midm[j] <- midmean(x,j)
> midm
[1] -0.4952103 -0.4383696 -0.4952103 -0.4383696 -0.4383696 -0.4952103 -0.4383696
[8] -0.4391737
> postscript(file="/var/www/html/rcomp/tmp/15zf31256053015.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/2yz741256053015.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/3neq91256053015.tab") 
> 
> system("convert tmp/15zf31256053015.ps tmp/15zf31256053015.png")
> system("convert tmp/2yz741256053015.ps tmp/2yz741256053015.png")
> 
> 
> proc.time()
   user  system elapsed 
  2.092   0.334   2.248