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)

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(0.2612954
+ ,0.1199274
+ ,0.0852586
+ ,0.0787527
+ ,0.0475989
+ ,0.0184526
+ ,-0.0770353
+ ,-0.0269715
+ ,0.7787045
+ ,-0.1638537
+ ,-0.1836121
+ ,-0.3507641
+ ,0.0075108
+ ,0.4577967
+ ,0.6827424
+ ,0.0616388
+ ,0.2385877
+ ,-0.4114253
+ ,-105949972354199.0000000
+ ,-0.2648054
+ ,0.1070291
+ ,0.1360179
+ ,-0.1300411
+ ,-0.0525067
+ ,0.2999522
+ ,-0.0058877
+ ,0.5082153
+ ,-0.2545075
+ ,0.2698511
+ ,0.2406800
+ ,-0.8312265
+ ,0.5704267
+ ,-0.0304595
+ ,-0.2219388
+ ,-0.0537610
+ ,-0.1964189
+ ,0.4362073
+ ,0.1386547
+ ,-0.2652463
+ ,-0.1002003
+ ,0.4426762
+ ,-0.0596184
+ ,0.1241996
+ ,-0.7183755
+ ,0.0384192
+ ,-0.0411679
+ ,0.1062431
+ ,-0.3550513
+ ,-0.1364715
+ ,0.5158243
+ ,0.4844733
+ ,-0.0873717
+ ,-0.4396326
+ ,-0.1563765
+ ,-0.3812771
+ ,-0.1394269
+ ,0.0062911
+ ,0.1457926
+ ,0.3852481
+ ,0.0586338
+ ,-0.0986281
+ ,-0.0997382
+ ,-0.2143859
+ ,0.1338376
+ ,0.0347307
+ ,0.2394928
+ ,-0.5775264
+ ,0.0199321
+ ,-0.0806811
+ ,-0.1985152
+ ,-0.3648308
+ ,0.2686832
+ ,-0.1742388
+ ,0.0603476
+ ,-0.5146724
+ ,-0.0254469
+ ,0.9590277
+ ,-0.2079646
+ ,0.4114399
+ ,-0.2411692
+ ,0.3869621
+ ,-0.3167880
+ ,0.0850939
+ ,0.3046019
+ ,0.2917561
+ ,0.4638277
+ ,-0.0853615
+ ,0.0856066
+ ,-0.1002348
+ ,0.1039727
+ ,-0.3306544
+ ,-0.4827168
+ ,0.2309593
+ ,0.5200578
+ ,0.1699253
+ ,-0.2429273
+ ,-0.2344870
+ ,0.0681538
+ ,0.2928410
+ ,-0.4215268
+ ,-0.4898912
+ ,0.2728075
+ ,-0.0234383
+ ,0.2437270
+ ,0.1441034
+ ,0.3486934
+ ,-0.2023078
+ ,-0.1854841
+ ,-0.0074343
+ ,-0.1426377
+ ,0.1094409
+ ,0.3583702
+ ,0.2211597
+ ,-0.0477162
+ ,-0.1248808
+ ,-0.0322416
+ ,-0.3191736
+ ,0.3667243
+ ,0.4848844
+ ,-0.0208251
+ ,0.5054507
+ ,0.0186890
+ ,0.2491611
+ ,-0.0125337
+ ,0.4052350
+ ,-0.0052602
+ ,0.2340145
+ ,-0.3319049
+ ,-0.3975116
+ ,-0.1006200
+ ,-0.0256229
+ ,0.3864107
+ ,0.2341884
+ ,0.2465479
+ ,-0.4497857
+ ,-0.1213249
+ ,-0.1753105
+ ,0.3623830
+ ,0.0572417
+ ,0.3763589
+ ,-0.2915969
+ ,-0.2416817
+ ,0.0162782
+ ,-0.1418666
+ ,-0.3654466
+ ,-0.7121934
+ ,0.4687787
+ ,0.3120325
+ ,0.1293531
+ ,0.1648593
+ ,-0.4758823
+ ,0.1885553
+ ,0.1991413
+ ,0.0473497
+ ,-0.1827396
+ ,0.1509197
+ ,-0.5510143
+ ,0.6503816
+ ,0.0566364
+ ,-0.4854993
+ ,-0.0237593
+ ,0.2340704
+ ,0.4182033
+ ,0.3923773
+ ,0.4896438
+ ,0.0558385
+ ,0.1073176
+ ,0.3541497
+ ,0.3202133
+ ,0.0060837
+ ,0.5006057
+ ,0.4108391
+ ,0.1220578
+ ,0.3928809
+ ,0.0194724
+ ,-0.2749880
+ ,-0.3323001
+ ,-0.8219820
+ ,-0.6250797
+ ,0.2913434
+ ,0.3276369
+ ,0.0527862
+ ,-0.0724262
+ ,-0.4526045
+ ,-0.1601941
+ ,-0.0564278
+ ,-0.0577598
+ ,-0.0998699
+ ,-0.0713135
+ ,0.1097104
+ ,0.2555912
+ ,-0.1260099
+ ,-0.2107783
+ ,0.1316683
+ ,0.1201368
+ ,0.2432284
+ ,-0.4117344
+ ,-0.2413680
+ ,0.3052385
+ ,0.0657756
+ ,-0.1488040
+ ,0.1193887
+ ,0.1256285
+ ,0.2601406
+ ,0.2637692
+ ,0.1564489
+ ,-0.4806378
+ ,-0.3081520
+ ,0.0356640
+ ,-0.5153010
+ ,-0.3240954
+ ,-0.1485235
+ ,0.2335331
+ ,0.4658222
+ ,0.2535112
+ ,-0.2585672
+ ,104562110333126.0000000
+ ,0.2992508
+ ,0.5151253
+ ,0.1458136
+ ,-0.0456761
+ ,-0.3869198
+ ,0.0220983
+ ,0.1746298
+ ,0.0153408
+ ,-0.0583372
+ ,0.6180818
+ ,-0.3458976
+ ,0.3066144
+ ,0.1971475
+ ,-0.1520329
+ ,0.6055431
+ ,0.0256170
+ ,-0.1293628
+ ,-0.6566055
+ ,-0.1435563
+ ,0.1165143
+ ,-0.0445963
+ ,0.2245579
+ ,-0.0519041
+ ,0.4250692
+ ,-0.0426066
+ ,-0.3579304
+ ,0.5294173
+ ,0.0245672
+ ,-0.0230731
+ ,-0.0722307
+ ,0.1362568
+ ,-0.0340457
+ ,0.3554641
+ ,-0.0014537
+ ,-0.0526226
+ ,0.5779047
+ ,0.1238081
+ ,0.3384949
+ ,0.2578782
+ ,-0.3197173
+ ,-0.0369641
+ ,0.2043844
+ ,-0.0281985
+ ,-0.0628542
+ ,-0.1879158
+ ,-0.1466980
+ ,0.5546829
+ ,0.0170458
+ ,0.1233742
+ ,0.1237018
+ ,-0.1105713
+ ,-0.2544327
+ ,-0.3824815
+ ,-0.2182999
+ ,0.0448819
+ ,0.2738115
+ ,0.2553722
+ ,-0.0033340
+ ,0.0779717
+ ,0.0317364
+ ,0.0759541
+ ,0.1211982
+ ,-0.4466220
+ ,-0.1410048
+ ,-0.1257054
+ ,-0.4218211
+ ,-0.1734130
+ ,-0.1822666
+ ,0.1446557
+ ,-0.2500324
+ ,0.4277234)
> 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] -4818965351
> sqrtn <- sqrt(length(x))
> (armse <- sd(x) / sqrtn)
[1] 517766813143
> (armose <- arm / armse)
[1] -0.009307212
> (geo <- geomean(x))
[1] NaN
Warning message:
In log(x) : NaNs produced
> (har <- harmean(x))
[1] -0.3113072
> (qua <- quamean(x))
[1] 8.771527e+12
> (win <- winmean(x))
            [,1]        [,2]
 [1,] 0.02482251 0.018006481
 [2,] 0.02363447 0.017789942
 [3,] 0.02371410 0.017481030
 [4,] 0.02335050 0.017410638
 [5,] 0.02375481 0.017204151
 [6,] 0.02415038 0.017084203
 [7,] 0.02463442 0.016857477
 [8,] 0.02516314 0.016743829
 [9,] 0.02578719 0.016558072
[10,] 0.02493174 0.016459915
[11,] 0.02552076 0.016315793
[12,] 0.02552736 0.016277141
[13,] 0.02562141 0.016260120
[14,] 0.02538657 0.016214077
[15,] 0.02549026 0.016172318
[16,] 0.02651431 0.016007219
[17,] 0.02603364 0.015923672
[18,] 0.02593391 0.015873051
[19,] 0.02636789 0.015822742
[20,] 0.02651490 0.015588436
[21,] 0.02632078 0.015565025
[22,] 0.02691645 0.015475600
[23,] 0.02645949 0.015426008
[24,] 0.02635893 0.015190744
[25,] 0.02671682 0.015048586
[26,] 0.02635159 0.014938131
[27,] 0.02621567 0.014904120
[28,] 0.02708723 0.014697115
[29,] 0.02646820 0.014628542
[30,] 0.02712441 0.014556175
[31,] 0.02683109 0.014472466
[32,] 0.02593477 0.014304835
[33,] 0.02643469 0.014248706
[34,] 0.02740065 0.014046890
[35,] 0.02738167 0.014036632
[36,] 0.02739266 0.014009758
[37,] 0.02709329 0.013833916
[38,] 0.02639973 0.013671842
[39,] 0.02588547 0.013614535
[40,] 0.02565947 0.013537441
[41,] 0.02647518 0.013394329
[42,] 0.02869778 0.013170484
[43,] 0.03036293 0.012892960
[44,] 0.03029314 0.012637679
[45,] 0.02866547 0.012489209
[46,] 0.02847613 0.012309529
[47,] 0.02780359 0.012146231
[48,] 0.02691304 0.012071954
[49,] 0.02742761 0.011992483
[50,] 0.02855061 0.011884740
[51,] 0.02794781 0.011800798
[52,] 0.02787780 0.011786124
[53,] 0.02673481 0.011689105
[54,] 0.02778430 0.011573459
[55,] 0.03010184 0.011380088
[56,] 0.02740043 0.011056644
[57,] 0.02797637 0.010981436
[58,] 0.02810751 0.010879534
[59,] 0.02844467 0.010817017
[60,] 0.02859942 0.010648620
[61,] 0.02887875 0.010547830
[62,] 0.02908143 0.010494908
[63,] 0.03044659 0.010318711
[64,] 0.03047874 0.010239954
[65,] 0.03085181 0.010205174
[66,] 0.03062528 0.010157887
[67,] 0.02972332 0.010072730
[68,] 0.03074873 0.009906152
[69,] 0.03032965 0.009836350
[70,] 0.03040918 0.009812655
[71,] 0.03213756 0.009595981
[72,] 0.03275566 0.009508603
[73,] 0.03349389 0.009423035
[74,] 0.03347958 0.009259349
[75,] 0.03428971 0.009198517
[76,] 0.03434898 0.009192268
[77,] 0.03470834 0.009148749
[78,] 0.03486215 0.009037346
[79,] 0.03335819 0.008887794
[80,] 0.03262844 0.008802407
[81,] 0.02815276 0.008437756
[82,] 0.02710920 0.008298117
[83,] 0.02738633 0.008197191
[84,] 0.02675580 0.007886908
[85,] 0.02284604 0.007582686
[86,] 0.02244244 0.007415079
[87,] 0.02100407 0.007303103
[88,] 0.01868618 0.007110473
[89,] 0.01807638 0.006918404
[90,] 0.01984122 0.006577696
[91,] 0.02297892 0.006362187
[92,] 0.02273880 0.006329456
[93,] 0.02257159 0.006316739
[94,] 0.02090103 0.006190877
[95,] 0.02015350 0.006135635
[96,] 0.02044390 0.006105213
> (tri <- trimean(x))
            [,1]        [,2]
 [1,] 0.02454924 0.017581070
 [2,] 0.02427212 0.017131641
 [3,] 0.02459773 0.016776706
 [4,] 0.02490069 0.016519355
 [5,] 0.02530217 0.016269615
 [6,] 0.02562510 0.016056185
 [7,] 0.02588345 0.015856500
 [8,] 0.02607237 0.015686709
 [9,] 0.02619361 0.015526541
[10,] 0.02624213 0.015384760
[11,] 0.02638401 0.015248855
[12,] 0.02646962 0.015123552
[13,] 0.02655594 0.014996627
[14,] 0.02663556 0.014865485
[15,] 0.02673515 0.014732620
[16,] 0.02682852 0.014597295
[17,] 0.02685079 0.014470200
[18,] 0.02690572 0.014344070
[19,] 0.02696792 0.014215933
[20,] 0.02700459 0.014085485
[21,] 0.02703326 0.013966608
[22,] 0.02707330 0.013843517
[23,] 0.02708179 0.013720717
[24,] 0.02711425 0.013595178
[25,] 0.02715234 0.013479492
[26,] 0.02717360 0.013367400
[27,] 0.02721251 0.013256730
[28,] 0.02725834 0.013142426
[29,] 0.02726599 0.013035227
[30,] 0.02730074 0.012926551
[31,] 0.02730823 0.012816457
[32,] 0.02732802 0.012705449
[33,] 0.02738450 0.012598388
[34,] 0.02742218 0.012488708
[35,] 0.02742302 0.012384725
[36,] 0.02742459 0.012275436
[37,] 0.02742579 0.012161447
[38,] 0.02743799 0.012051015
[39,] 0.02747547 0.011943381
[40,] 0.02753192 0.011832642
[41,] 0.02759736 0.011719672
[42,] 0.02763600 0.011608009
[43,] 0.02759996 0.011502099
[44,] 0.02750743 0.011404963
[45,] 0.02741534 0.011315663
[46,] 0.02737452 0.011228755
[47,] 0.02733897 0.011145887
[48,] 0.02732414 0.011066298
[49,] 0.02733712 0.010985385
[50,] 0.02733429 0.010903293
[51,] 0.02729663 0.010821380
[52,] 0.02727664 0.010738361
[53,] 0.02725835 0.010650420
[54,] 0.02727415 0.010561621
[55,] 0.02725887 0.010472858
[56,] 0.02717428 0.010388181
[57,] 0.02716760 0.010314748
[58,] 0.02714384 0.010239857
[59,] 0.02711569 0.010164796
[60,] 0.02707708 0.010087396
[61,] 0.02703306 0.010013159
[62,] 0.02697992 0.009938577
[63,] 0.02691966 0.009860989
[64,] 0.02681890 0.009786825
[65,] 0.02671466 0.009710976
[66,] 0.02659715 0.009630815
[67,] 0.02648302 0.009546734
[68,] 0.02639138 0.009460620
[69,] 0.02626835 0.009376838
[70,] 0.02615381 0.009290001
[71,] 0.02603390 0.009197055
[72,] 0.02586196 0.009108865
[73,] 0.02566777 0.009018032
[74,] 0.02544723 0.008924156
[75,] 0.02522071 0.008831935
[76,] 0.02496464 0.008734820
[77,] 0.02469925 0.008628952
[78,] 0.02441564 0.008515834
[79,] 0.02411894 0.008399391
[80,] 0.02385579 0.008282384
[81,] 0.02360515 0.008160013
[82,] 0.02347475 0.008052358
[83,] 0.02337012 0.007943839
[84,] 0.02325399 0.007831382
[85,] 0.02315224 0.007730124
[86,] 0.02316118 0.007640580
[87,] 0.02318230 0.007553448
[88,] 0.02324668 0.007464721
[89,] 0.02338236 0.007380124
[90,] 0.02354134 0.007300131
[91,] 0.02365305 0.007236868
[92,] 0.02367356 0.007182029
[93,] 0.02370225 0.007122029
[94,] 0.02373726 0.007054642
[95,] 0.02382593 0.006988144
[96,] 0.02394190 0.006916699
> (midr <- midrange(x))
[1] -6.93931e+11
> midm <- array(NA,dim=8)
> for (j in 1:8) midm[j] <- midmean(x,j)
> midm
[1] 0.02455358 0.02586196 0.02455358 0.02586196 0.02586196 0.02455358 0.02586196
[8] 0.02603390
> postscript(file="/var/wessaorg/rcomp/tmp/1tl5k1324568936.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/2nsjz1324568936.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/3el201324568936.tab") 
> 
> try(system("convert tmp/1tl5k1324568936.ps tmp/1tl5k1324568936.png",intern=TRUE))
character(0)
> try(system("convert tmp/2nsjz1324568936.ps tmp/2nsjz1324568936.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.740   0.161   1.899