R version 2.15.2 (2012-10-26) -- "Trick or Treat"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-pc-linux-gnu (32-bit)

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(-2.716932667
+ ,0.695354701
+ ,2.465773394
+ ,3.756800929
+ ,-1.889687332
+ ,-1.342423946
+ ,4.161807991
+ ,-1.656841747
+ ,-1.614396605
+ ,1.160117737
+ ,1.47558678
+ ,0.038654809
+ ,1.034583103
+ ,0.869405423
+ ,-0.726605178
+ ,-0.007360227
+ ,0.966688731
+ ,3.960453337
+ ,2.905813838
+ ,0.813862378
+ ,0.998463167
+ ,1.416135174
+ ,2.773099012
+ ,1.361748946
+ ,1.158397864
+ ,1.165514867
+ ,1.470598801
+ ,-1.416929777
+ ,0.704482544
+ ,0.382605544
+ ,-0.36723147
+ ,-0.157794884
+ ,-0.467033523
+ ,0.450952519
+ ,-1.151997771
+ ,-2.454806771
+ ,-2.290802595
+ ,-1.44287535
+ ,1.88743235
+ ,1.949699309
+ ,1.640084339
+ ,-1.412909516
+ ,2.502440756
+ ,0.262000289
+ ,-0.139025784
+ ,-4.150559388
+ ,-2.419095997
+ ,0.218766088
+ ,0.808402277
+ ,-1.361515364
+ ,-0.853739839
+ ,0.268310726
+ ,-2.61386536
+ ,0.409310097
+ ,-1.713731807
+ ,2.167395395
+ ,0.30627631
+ ,0.769644429
+ ,0.176995441
+ ,2.206777551
+ ,1.163272051
+ ,0.562135982
+ ,-0.29898697
+ ,-0.438887734
+ ,0.84995573
+ ,1.256146159
+ ,1.909653498
+ ,3.923509508
+ ,-3.808460881
+ ,0.527152017
+ ,-3.012245827
+ ,-0.715665538
+ ,1.162010456
+ ,0.807171814
+ ,0.990531311
+ ,3.909747507
+ ,-0.407232544
+ ,1.787718277
+ ,-1.961485328
+ ,0.916861489
+ ,0.463901031
+ ,0.356770523
+ ,-0.620182287
+ ,0.313856292
+ ,2.117237372
+ ,0.048211388
+ ,0.766905814
+ ,1.318697005
+ ,0.896661826
+ ,-1.643303567
+ ,0.167875359
+ ,0.270514769
+ ,0.094207665
+ ,-1.836456819
+ ,1.301967194
+ ,0.303921953
+ ,2.516715321
+ ,0.169958299
+ ,-0.266125863
+ ,-1.194086507
+ ,1.494098871
+ ,2.420900716
+ ,0.977353986
+ ,1.161623748
+ ,-1.712444774
+ ,1.239562685
+ ,0.227935475
+ ,1.767395736
+ ,-0.002480266
+ ,0.82816145
+ ,0.061511967
+ ,2.137467172
+ ,-1.528640241
+ ,-2.614568461
+ ,1.723547556
+ ,-1.950475963
+ ,1.007537805
+ ,-1.785824239
+ ,0.485542044
+ ,-1.373030868
+ ,0.592730467
+ ,-2.900148395
+ ,-1.073803686
+ ,-0.998565253
+ ,-0.921755895
+ ,0.249852821
+ ,1.23278974
+ ,0.995768005
+ ,-2.745597967
+ ,2.098177534
+ ,-3.490018923
+ ,2.515270651
+ ,-2.131895571
+ ,-1.689160164
+ ,-0.134952532
+ ,1.120129701
+ ,0.459324011
+ ,-2.363957787
+ ,-0.99487178
+ ,-2.279773405
+ ,3.129332967
+ ,1.422202992
+ ,-0.012629669
+ ,1.782276715
+ ,-3.307648252
+ ,2.289181735
+ ,-2.057515845
+ ,1.0801914
+ ,0.362236196
+ ,-2.878325739
+ ,-1.155043271
+ ,2.007639148
+ ,4.295954949
+ ,1.750032454
+ ,-2.310629981
+ ,0.167875359
+ ,1.430460681
+ ,0.995768005
+ ,1.32860448
+ ,-0.573651755
+ ,0.399396308
+ ,0.533448646
+ ,-0.388160789
+ ,0.426210073
+ ,1.327399554
+ ,-1.420672833
+ ,-0.469161997
+ ,-3.29098658
+ ,-1.848292762
+ ,1.569125254
+ ,1.634688184
+ ,0.294051606
+ ,-1.988393653
+ ,-2.312033591
+ ,-3.288588788
+ ,0.255786884
+ ,-0.263297297
+ ,-0.687934672
+ ,-0.062106612
+ ,-1.476269705
+ ,0.565951923
+ ,-0.521748993
+ ,1.839536729
+ ,-0.520609608
+ ,-6.76628809
+ ,1.03190728
+ ,2.252323131
+ ,-0.541803289
+ ,-0.526967526
+ ,0.700677591
+ ,-1.044903908
+ ,0.145076363
+ ,2.342000107
+ ,1.699486741
+ ,-0.915984634
+ ,-0.368633528
+ ,2.901656852
+ ,0.687030247
+ ,1.512544799
+ ,1.229420219
+ ,1.804610223
+ ,0.434739187
+ ,-2.762297678
+ ,-2.916569977
+ ,2.030333482
+ ,0.16303558
+ ,1.152973504
+ ,0.56605129
+ ,-2.916763144
+ ,0.69684053
+ ,-2.507489607
+ ,-4.289684969
+ ,0.690829519
+ ,2.832504112
+ ,1.116710656
+ ,0.579212169
+ ,1.937338022
+ ,-0.32791694
+ ,1.009711098
+ ,-0.615891961
+ ,-2.022491333
+ ,-0.573303347
+ ,0.433554087
+ ,-1.45853137
+ ,0.19571926
+ ,-3.966868429
+ ,-0.309683138
+ ,0.726256447
+ ,-1.343269573
+ ,-1.160998557
+ ,1.520067648
+ ,-3.465040334
+ ,4.299546178
+ ,1.544133629
+ ,-1.305398824
+ ,-2.654920743
+ ,-7.170028137
+ ,-1.815214028
+ ,1.407636695
+ ,-1.928726129
+ ,-0.407197066
+ ,-1.795600382
+ ,1.113655299
+ ,1.72299312
+ ,0.907372684
+ ,-0.046770178
+ ,0.846117134
+ ,-2.890292844
+ ,1.19903418
+ ,0.116066371
+ ,-1.137919803
+ ,-1.862263458
+ ,0.336856218
+ ,2.821775236
+ ,-1.715206305
+ ,-0.26408786
+ ,1.318811443
+ ,2.176071319
+ ,-1.781640984
+ ,-5.483306743
+ ,0.825633349
+ ,-4.550209689
+ ,-0.471645252
+ ,0.832709147)
> ylimmax = ''
> ylimmin = ''
> main = 'Robustness of Central Tendency'
> #'GNU S' R Code compiled by R2WASP v. 1.2.291 ()
> #Author: root
> #To cite this work: Wessa, P., (2012), Central Tendency (v1.0.4) 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
> #
> 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] 1.136364e-11
> sqrtn <- sqrt(length(x))
> (armse <- sd(x) / sqrtn)
[1] 0.1144268
> (armose <- arm / armse)
[1] 9.93093e-11
> (geo <- geomean(x))
[1] NaN
Warning message:
In log(x) : NaNs produced
> (har <- harmean(x))
[1] -0.5388881
> (qua <- quamean(x))
[1] 1.85569
> (win <- winmean(x))
             [,1]       [,2]
 [1,] 0.001515715 0.11407012
 [2,] 0.010219006 0.11192060
 [3,] 0.018534261 0.10977307
 [4,] 0.021921850 0.10908780
 [5,] 0.024296160 0.10866189
 [6,] 0.024994896 0.10759690
 [7,] 0.012557688 0.10497179
 [8,] 0.015434137 0.10293470
 [9,] 0.016143965 0.10280962
[10,] 0.019486364 0.10177784
[11,] 0.019733564 0.10164478
[12,] 0.017629999 0.10140101
[13,] 0.018612842 0.09849919
[14,] 0.023599706 0.09790646
[15,] 0.022881710 0.09783481
[16,] 0.021654693 0.09750829
[17,] 0.019399802 0.09716253
[18,] 0.014836154 0.09657034
[19,] 0.019385337 0.09528486
[20,] 0.017858148 0.09489314
[21,] 0.016515398 0.09431913
[22,] 0.019124206 0.09352834
[23,] 0.021883889 0.09308168
[24,] 0.019227059 0.09283755
[25,] 0.027384820 0.09159811
[26,] 0.030696176 0.09089280
[27,] 0.027409818 0.08992009
[28,] 0.030850835 0.08911538
[29,] 0.030190026 0.08800299
[30,] 0.028944835 0.08787060
[31,] 0.028022217 0.08736794
[32,] 0.026665616 0.08701332
[33,] 0.039163392 0.08469521
[34,] 0.044244489 0.08340714
[35,] 0.046648428 0.08278464
[36,] 0.050556080 0.08228529
[37,] 0.052241731 0.08176444
[38,] 0.051327152 0.08141736
[39,] 0.050627654 0.08080836
[40,] 0.056458617 0.08025359
[41,] 0.057067016 0.07957456
[42,] 0.049839245 0.07863644
[43,] 0.050888150 0.07839218
[44,] 0.043501460 0.07723804
[45,] 0.042584759 0.07661388
[46,] 0.040094863 0.07614734
[47,] 0.039500314 0.07598060
[48,] 0.048225541 0.07464046
[49,] 0.045063261 0.07436366
[50,] 0.044362324 0.07427270
[51,] 0.041106533 0.07330609
[52,] 0.045845767 0.07261946
[53,] 0.047345499 0.07228972
[54,] 0.051519961 0.07164028
[55,] 0.059825922 0.06938759
[56,] 0.063904180 0.06792550
[57,] 0.067473893 0.06757756
[58,] 0.069026691 0.06714902
[59,] 0.073963042 0.06672350
[60,] 0.071011507 0.06638212
[61,] 0.061352995 0.06556273
[62,] 0.066823831 0.06449527
[63,] 0.067955578 0.06415056
[64,] 0.071561947 0.06372004
[65,] 0.064288739 0.06318856
[66,] 0.065165191 0.06183714
[67,] 0.092845709 0.05944479
[68,] 0.101043406 0.05872349
[69,] 0.102498830 0.05858944
[70,] 0.102907028 0.05849611
[71,] 0.106230606 0.05815590
[72,] 0.122237449 0.05664054
[73,] 0.121146867 0.05537408
[74,] 0.133177363 0.05427322
[75,] 0.133358646 0.05413026
[76,] 0.144773612 0.05180986
[77,] 0.133154476 0.05077217
[78,] 0.150754400 0.04928340
[79,] 0.182156445 0.04592319
[80,] 0.184812914 0.04562896
[81,] 0.190536984 0.04480165
[82,] 0.210744151 0.04318955
[83,] 0.212093004 0.04309094
[84,] 0.223866849 0.04199928
[85,] 0.219736326 0.04169738
[86,] 0.226523421 0.04071813
[87,] 0.214992138 0.03924102
[88,] 0.213568714 0.03890118
> (tri <- trimean(x))
            [,1]       [,2]
 [1,] 0.01095604 0.11077880
 [2,] 0.02054160 0.10726947
 [3,] 0.02582292 0.10474046
 [4,] 0.02832840 0.10288361
 [5,] 0.02999309 0.10112597
 [6,] 0.03118674 0.09937538
 [7,] 0.03227650 0.09774798
 [8,] 0.03527521 0.09650013
 [9,] 0.03793682 0.09550746
[10,] 0.04055673 0.09448193
[11,] 0.04285531 0.09353829
[12,] 0.04516749 0.09256204
[13,] 0.04771297 0.09156225
[14,] 0.05021702 0.09081781
[15,] 0.05236201 0.09009353
[16,] 0.05459844 0.08933751
[17,] 0.05696180 0.08857053
[18,] 0.05952020 0.08779204
[19,] 0.06242005 0.08702036
[20,] 0.06508950 0.08631134
[21,] 0.06789785 0.08559335
[22,] 0.07083399 0.08487862
[23,] 0.07368040 0.08418255
[24,] 0.07643287 0.08347940
[25,] 0.07937336 0.08275246
[26,] 0.08196297 0.08207085
[27,] 0.08444181 0.08139762
[28,] 0.08712280 0.08074875
[29,] 0.08969835 0.08011405
[30,] 0.09235390 0.07951209
[31,] 0.09511627 0.07888095
[32,] 0.09797318 0.07824185
[33,] 0.10094433 0.07758427
[34,] 0.10346600 0.07702950
[35,] 0.10583630 0.07651663
[36,] 0.10816154 0.07600685
[37,] 0.11038490 0.07549272
[38,] 0.11259160 0.07497435
[39,] 0.11487992 0.07444044
[40,] 0.11724371 0.07390479
[41,] 0.11944801 0.07336475
[42,] 0.12167952 0.07282582
[43,] 0.12421642 0.07230077
[44,] 0.12677438 0.07175164
[45,] 0.12964586 0.07122663
[46,] 0.13261539 0.07069760
[47,] 0.13573884 0.07015435
[48,] 0.13895655 0.06957876
[49,] 0.14196269 0.06903840
[50,] 0.14514605 0.06847049
[51,] 0.14843085 0.06786251
[52,] 0.15190311 0.06726160
[53,] 0.15531099 0.06665389
[54,] 0.15875836 0.06601629
[55,] 0.16216276 0.06536627
[56,] 0.16539445 0.06479958
[57,] 0.16858414 0.06427203
[58,] 0.17174833 0.06371967
[59,] 0.17495080 0.06314441
[60,] 0.17808884 0.06254516
[61,] 0.18140673 0.06191151
[62,] 0.18511799 0.06126711
[63,] 0.18876802 0.06063274
[64,] 0.19249053 0.05996069
[65,] 0.19621315 0.05925405
[66,] 0.20027236 0.05851038
[67,] 0.20442951 0.05778539
[68,] 0.20786445 0.05716439
[69,] 0.21115586 0.05653222
[70,] 0.21450853 0.05584391
[71,] 0.21795851 0.05508983
[72,] 0.22142050 0.05428216
[73,] 0.22450246 0.05350950
[74,] 0.22772469 0.05274725
[75,] 0.23068350 0.05199067
[76,] 0.23374228 0.05115915
[77,] 0.23655182 0.05042375
[78,] 0.23983427 0.04967781
[79,] 0.24267862 0.04897396
[80,] 0.24462334 0.04847034
[81,] 0.24655839 0.04792523
[82,] 0.24838427 0.04737871
[83,] 0.24962083 0.04690035
[84,] 0.25086422 0.04636313
[85,] 0.25176687 0.04584896
[86,] 0.25284821 0.04528599
[87,] 0.25374611 0.04473303
[88,] 0.25508245 0.04423235
> (midr <- midrange(x))
[1] -1.435241
> midm <- array(NA,dim=8)
> for (j in 1:8) midm[j] <- midmean(x,j)
> midm
[1] 0.1886731 0.2002724 0.1886731 0.2002724 0.2002724 0.1886731 0.2002724
[8] 0.1962131
> postscript(file="/var/wessaorg/rcomp/tmp/1xnk51356031996.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/2yobw1356031996.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/3rvf41356031996.tab") 
> 
> try(system("convert tmp/1xnk51356031996.ps tmp/1xnk51356031996.png",intern=TRUE))
character(0)
> try(system("convert tmp/2yobw1356031996.ps tmp/2yobw1356031996.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.632   0.360   2.966