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.

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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(-0.570875874954911
+ ,-0.511137633876425
+ ,-1.02711574887165
+ ,-0.247459135140635
+ ,-0.595944868112521
+ ,-0.681163109535305
+ ,0.345185635144615
+ ,1.51024603582169
+ ,-0.418019414772234
+ ,-0.311267072375839
+ ,1.67163081198947
+ ,-0.539506946905068
+ ,1.40945065934532
+ ,2.2420522686079
+ ,1.1650962896284
+ ,2.42060649786476
+ ,0.0682279397221915
+ ,-0.11067421906174
+ ,0.024453242603238
+ ,-0.497693857719122
+ ,-0.595630964725977
+ ,0.115390547461763
+ ,-0.675239658349256
+ ,-0.57778043034228
+ ,0.50210834818284
+ ,0.283004867702643
+ ,0.430374653934966
+ ,-0.695202084018761
+ ,-0.430981910529177
+ ,-0.970212998970839
+ ,-1.10289156964033
+ ,-0.506294026344613
+ ,-1.1356372838091
+ ,-0.716198265950065
+ ,2.38909456645549
+ ,0.766445974578577
+ ,0.20101606034162
+ ,0.938576757692077
+ ,-0.975096254853228
+ ,-0.0782947847538538
+ ,0.215600369809319
+ ,1.11394756921882
+ ,1.6878843005693
+ ,0.740961084054461
+ ,-0.278511975869071
+ ,0.105272624006693
+ ,-0.871792516446899
+ ,1.03273141271
+ ,1.15764643511619
+ ,-1.36281718857765
+ ,-1.22079671087844
+ ,3.02664994074065
+ ,-1.14348881138996
+ ,-1.01628030645187
+ ,-0.954424929131502
+ ,-0.21738667106372
+ ,-0.949233018879874
+ ,-1.04076580006722
+ ,-0.86871330354106
+ ,-0.895786571506119
+ ,-1.38421385241876
+ ,-0.502591734605609
+ ,-0.979653837088994
+ ,-0.756778917390011
+ ,-1.02509893199872
+ ,0.775078491645856
+ ,-0.577057910071895
+ ,-1.13886240901432
+ ,0.62205809771103
+ ,-0.265105972838122
+ ,2.87802336297808
+ ,-0.382208027407422
+ ,-0.803820507579544
+ ,-0.136143485767757
+ ,1.1797677238516
+ ,3.99082323347408
+ ,-0.600638307090792
+ ,-0.311939888127828
+ ,1.33010622026773
+ ,-0.0109999670812058
+ ,0.0925603270401305
+ ,0.0666536056689318
+ ,-0.0976293348785303
+ ,0.123635635988901
+ ,-0.518466391586699
+ ,-0.697414295956901
+ ,-1.26611290183839
+ ,0.516880230125759
+ ,0.763210392895926
+ ,-3.17516924292666
+ ,0.301867748783821
+ ,1.24353362687794
+ ,0.356838232267432
+ ,0.804523450098973
+ ,-0.736843535921125
+ ,1.45248739251206
+ ,-0.183442920152471
+ ,-1.32915521507038
+ ,0.505243391464097
+ ,-0.252827982423921
+ ,-0.0820050030754919
+ ,0.806423061579241
+ ,-1.33566333741937
+ ,11.4870981436885
+ ,0.143480495184982
+ ,-0.629857613263178
+ ,-0.278502748669541
+ ,-0.0922405695467127
+ ,0.331799201089393
+ ,-0.641972295179589
+ ,-0.52925336602269
+ ,-0.292544657144514
+ ,-0.48090361413658
+ ,-0.231631079662059
+ ,-0.546752715146306
+ ,-0.0781488200211302
+ ,-1.42330899184991
+ ,4.74593671144418
+ ,-1.03729791587256
+ ,1.1870975602054
+ ,-1.48483448678642
+ ,-1.11006560160739
+ ,0.602873113818105
+ ,0.393348983328672
+ ,-0.962148755968666
+ ,0.0184697158565785
+ ,-0.563883593450448
+ ,0.166315739043732
+ ,-1.08186987396044
+ ,-1.18733053107029
+ ,0.237743031994863
+ ,0.611036185140024
+ ,-0.79400692107665
+ ,0.278478683949076
+ ,-0.40622276355127
+ ,0.925398335411391
+ ,-1.19614998561647
+ ,-1.08864464497138
+ ,0.106042607339614
+ ,-0.937805020621083
+ ,-0.951761263569382
+ ,0.595660179931811
+ ,-2.62322849033463
+ ,2.06484177835207
+ ,-1.15690136846534
+ ,-0.971783998547422
+ ,-0.611926215083187
+ ,-0.674696186077007
+ ,-0.343071672001661
+ ,0.0120489059140767
+ ,-0.1383795628118
+ ,-0.749301027572427
+ ,-0.0329519337637752
+ ,-1.09832797043057
+ ,-1.17865313545005
+ ,-1.02319960877937
+ ,-0.63343703425983
+ ,-0.667677699369087
+ ,0.242137116993484
+ ,-0.237785307537331
+ ,-1.28283276733994
+ ,-0.319221905012263
+ ,-1.07577434747054
+ ,-1.13649959159528
+ ,-0.716757290883056
+ ,0.0050195699244691
+ ,-0.504182930963768
+ ,1.13739429185878
+ ,-0.794477152263173
+ ,-0.676009433293868
+ ,-0.129975959035785
+ ,-1.27220519162244
+ ,-0.755237196212232
+ ,3.62224545199573
+ ,-0.560259328998728
+ ,-0.250527785501192
+ ,-0.958991696990211
+ ,0.708498584924803
+ ,3.30076531741245
+ ,-0.937278704405174
+ ,-0.46112570699458
+ ,-1.35080551053675
+ ,-0.387951998968327
+ ,-0.132809676479671
+ ,0.686880241158722
+ ,-1.14841695968091
+ ,-0.198286402619942
+ ,-0.953424606143797
+ ,-0.831357405076732
+ ,22.7625252139011
+ ,4.34870014838875
+ ,-0.319775027225167
+ ,0.97886788111642
+ ,0.325925998526894
+ ,-0.110945361117234
+ ,-0.365480129339294
+ ,-0.288011496869506
+ ,-0.710975104172849
+ ,-1.8080416080161
+ ,-0.235072089058427
+ ,0.13336071414661
+ ,-0.481494207191557
+ ,-0.206654552341621
+ ,-0.71794143881947
+ ,-0.535845992452363
+ ,-0.64391059755181
+ ,0.205363138599996
+ ,0.0508051028472974
+ ,2.76211043555277
+ ,0.133938984226997
+ ,1.88662225519968
+ ,0.381866764736397
+ ,-0.827580442911865
+ ,-0.81926704434319
+ ,-1.17447429123239
+ ,-1.06053401149788
+ ,0.362718967032987
+ ,-0.607230297987153
+ ,-0.795842078874565
+ ,2.19018109168148
+ ,-0.960928566996128
+ ,0.695807217144514
+ ,2.9531433869023
+ ,0.449333749972229
+ ,0.936197534191918
+ ,0.00708092406711823
+ ,-1.0470414190653
+ ,-0.309764250493209
+ ,0.56233230889481
+ ,0.52203654340317
+ ,1.48231766408574
+ ,-2.07880984858141
+ ,0.296482095485587
+ ,-0.891179833788977
+ ,0.80794132077361
+ ,-0.552056351725605
+ ,-0.552867908673155
+ ,0.54325251003202
+ ,-0.542639108993608
+ ,-1.14471096835535
+ ,0.897529324353421
+ ,-0.0587815608245133
+ ,-1.07951863367864
+ ,-0.321172778596499
+ ,3.63437594437048
+ ,-0.947415480617462
+ ,-0.444699816200167
+ ,-0.565734426226205
+ ,-1.0922253156685
+ ,-0.459435345163184
+ ,-0.142489401411015
+ ,-0.97883583888393
+ ,-0.128394706781461
+ ,-0.844820295970723
+ ,-0.449188164589142
+ ,2.69711549482262
+ ,-0.833866835914459
+ ,0.798123612465257
+ ,-1.56644291213894
+ ,-0.858564280379805
+ ,-1.23272160763895
+ ,0.552974531733387
+ ,-1.08885968599948
+ ,-0.9105726069444
+ ,-0.467094210025088
+ ,-0.144975212059016
+ ,0.368273096383276
+ ,-1.02227305524387
+ ,-0.178894554646343
+ ,-0.956520150164327
+ ,0.993268299278574
+ ,-0.0751935665325974
+ ,-0.247427657865658
+ ,-1.04209423708647
+ ,-1.43838747724043
+ ,-0.868914642846923
+ ,-0.373821984452502
+ ,-0.95991791584591
+ ,-1.06980573040423
+ ,0.289510851234438
+ ,-0.978451460994812
+ ,0.0320063620547714
+ ,-1.04991171481537
+ ,2.22634733938379
+ ,0.0845744976638473
+ ,-0.268053463733876
+ ,0.849962268527854
+ ,0.0927671230687298
+ ,-1.00214059100251)
> 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] -1.323927e-18
> sqrtn <- sqrt(length(x))
> (armse <- sd(x) / sqrtn)
[1] 0.1098082
> (armose <- arm / armse)
[1] -1.205672e-17
> (geo <- geomean(x))
[1] NaN
Warning message:
In log(x) : NaNs produced
> (har <- harmean(x))
[1] 1.105706
> (qua <- quamean(x))
[1] 1.863508
> (win <- winmean(x))
             [,1]       [,2]
 [1,] -0.03710549 0.08587681
 [2,] -0.07998952 0.06831086
 [3,] -0.08130234 0.06706331
 [4,] -0.08291173 0.06568073
 [5,] -0.08766673 0.06428768
 [6,] -0.08695427 0.06416544
 [7,] -0.09437577 0.06262366
 [8,] -0.10088152 0.06115598
 [9,] -0.10250432 0.06070438
[10,] -0.10468800 0.06022380
[11,] -0.10852356 0.05943306
[12,] -0.11095208 0.05896424
[13,] -0.12130649 0.05681997
[14,] -0.12231819 0.05654726
[15,] -0.12963394 0.05536859
[16,] -0.12865476 0.05510924
[17,] -0.13008072 0.05474621
[18,] -0.13635223 0.05350818
[19,] -0.14748926 0.05183233
[20,] -0.16064224 0.04996883
[21,] -0.16151964 0.04979603
[22,] -0.17246725 0.04817042
[23,] -0.17401470 0.04785423
[24,] -0.17618419 0.04753624
[25,] -0.17980136 0.04708915
[26,] -0.18652340 0.04623459
[27,] -0.19439075 0.04531237
[28,] -0.19977506 0.04471058
[29,] -0.19794456 0.04444671
[30,] -0.19872284 0.04423026
[31,] -0.19903244 0.04411011
[32,] -0.20059916 0.04382372
[33,] -0.20289216 0.04351398
[34,] -0.21242170 0.04252427
[35,] -0.21638050 0.04198351
[36,] -0.21788143 0.04178361
[37,] -0.22256044 0.04124056
[38,] -0.22208848 0.04115373
[39,] -0.22229461 0.04092232
[40,] -0.22468170 0.04044431
[41,] -0.23102276 0.03977182
[42,] -0.23641064 0.03914949
[43,] -0.23643889 0.03911446
[44,] -0.23620012 0.03905003
[45,] -0.23561118 0.03884533
[46,] -0.23895824 0.03848532
[47,] -0.24005326 0.03833520
[48,] -0.24043677 0.03827533
[49,] -0.24319307 0.03786129
[50,] -0.24636310 0.03718438
[51,] -0.24463450 0.03670692
[52,] -0.24609356 0.03655406
[53,] -0.25791086 0.03551071
[54,] -0.25934340 0.03528976
[55,] -0.26026656 0.03511257
[56,] -0.26135981 0.03497204
[57,] -0.26634260 0.03430469
[58,] -0.26797575 0.03413024
[59,] -0.26975420 0.03395029
[60,] -0.27396660 0.03357224
[61,] -0.27453328 0.03344579
[62,] -0.27658027 0.03320935
[63,] -0.27704563 0.03313806
[64,] -0.28836438 0.03216929
[65,] -0.29205990 0.03179052
[66,] -0.30010051 0.03109963
[67,] -0.30053445 0.03073324
[68,] -0.30360912 0.03047860
[69,] -0.29855900 0.02992035
[70,] -0.29640200 0.02955777
[71,] -0.29813299 0.02925898
[72,] -0.29663796 0.02866652
[73,] -0.29739457 0.02850311
[74,] -0.30350326 0.02803466
[75,] -0.30226709 0.02774603
[76,] -0.30048602 0.02735804
[77,] -0.29930106 0.02702728
[78,] -0.29984537 0.02688947
[79,] -0.30874711 0.02608309
[80,] -0.30766218 0.02583532
[81,] -0.30953895 0.02508533
[82,] -0.31017986 0.02471993
[83,] -0.31103632 0.02460288
[84,] -0.32098555 0.02387152
[85,] -0.31675239 0.02265038
[86,] -0.31913295 0.02241964
[87,] -0.31752002 0.02228696
[88,] -0.31668800 0.02182485
[89,] -0.31340609 0.02126012
[90,] -0.31594844 0.02103240
[91,] -0.31601487 0.02100387
[92,] -0.31833312 0.02061745
[93,] -0.31403581 0.02032564
[94,] -0.31591374 0.02009844
[95,] -0.31667228 0.01942615
[96,] -0.31548330 0.01927882
> (tri <- trimean(x))
             [,1]       [,2]
 [1,] -0.06824863 0.07599537
 [2,] -0.09982886 0.06421002
 [3,] -0.10995884 0.06195032
 [4,] -0.11978296 0.06002590
 [5,] -0.12933115 0.05839419
 [6,] -0.13802503 0.05700699
 [7,] -0.14697015 0.05556023
 [8,] -0.15492398 0.05431545
 [9,] -0.16212798 0.05324255
[10,] -0.16924539 0.05217617
[11,] -0.17623306 0.05111536
[12,] -0.18294594 0.05009636
[13,] -0.18953853 0.04907569
[14,] -0.19535022 0.04824321
[15,] -0.20117103 0.04739323
[16,] -0.20653400 0.04661761
[17,] -0.21205044 0.04582281
[18,] -0.21755829 0.04501702
[19,] -0.22275275 0.04427905
[20,] -0.22735032 0.04364762
[21,] -0.23125288 0.04313735
[22,] -0.23516987 0.04261316
[23,] -0.23855952 0.04218599
[24,] -0.24192475 0.04175907
[25,] -0.24192475 0.04133209
[26,] -0.24842870 0.04091377
[27,] -0.25135679 0.04053201
[28,] -0.25397373 0.04019161
[29,] -0.25639541 0.03987200
[30,] -0.25893905 0.03955046
[31,] -0.26149448 0.03922428
[32,] -0.26408251 0.03888696
[33,] -0.26665352 0.03854796
[34,] -0.26918019 0.03820847
[35,] -0.27138315 0.03790969
[36,] -0.27347607 0.03762531
[37,] -0.27555189 0.03733574
[38,] -0.27749511 0.03706045
[39,] -0.27949218 0.03677322
[40,] -0.28152017 0.03648136
[41,] -0.28350402 0.03619846
[42,] -0.28530856 0.03593615
[43,] -0.28696601 0.03569194
[44,] -0.28865551 0.03543400
[45,] -0.29038685 0.03516289
[46,] -0.29217255 0.03488504
[47,] -0.29388703 0.03460923
[48,] -0.29560216 0.03432357
[49,] -0.29734112 0.03402228
[50,] -0.29734112 0.03372397
[51,] -0.30065879 0.03344274
[52,] -0.30237485 0.03316725
[53,] -0.30408411 0.03288117
[54,] -0.30547513 0.03263384
[55,] -0.30685440 0.03238084
[56,] -0.30823744 0.03211925
[57,] -0.30961985 0.03184644
[58,] -0.31088820 0.03159082
[59,] -0.31213862 0.03132594
[60,] -0.31336709 0.03105139
[61,] -0.31336709 0.03077780
[62,] -0.31565117 0.03049038
[63,] -0.31676848 0.03019452
[64,] -0.31790028 0.02987974
[65,] -0.31873911 0.02959803
[66,] -0.31949465 0.02931604
[67,] -0.32004254 0.02905198
[68,] -0.32059252 0.02878722
[69,] -0.32107052 0.02851549
[70,] -0.32170333 0.02825277
[71,] -0.32241393 0.02798840
[72,] -0.32309554 0.02771901
[73,] -0.32383818 0.02746108
[74,] -0.32458065 0.02718990
[75,] -0.32517285 0.02692397
[76,] -0.32581710 0.02665116
[77,] -0.32581710 0.02637690
[78,] -0.32729904 0.02609741
[79,] -0.32807552 0.02579998
[80,] -0.32862364 0.02552874
[81,] -0.32921989 0.02524668
[82,] -0.32978165 0.02498707
[83,] -0.33034331 0.02472540
[84,] -0.33089889 0.02444431
[85,] -0.33118550 0.02418645
[86,] -0.33160492 0.02398529
[87,] -0.33196937 0.02377700
[88,] -0.33239414 0.02355321
[89,] -0.33285883 0.02333637
[90,] -0.33343834 0.02313397
[91,] -0.33396322 0.02292343
[92,] -0.33450608 0.02268791
[93,] -0.33499932 0.02245341
[94,] -0.33564432 0.02221066
[95,] -0.33625706 0.02195496
[96,] -0.33687128 0.02172233
> (midr <- midrange(x))
[1] 9.793678
> midm <- array(NA,dim=8)
> for (j in 1:8) midm[j] <- midmean(x,j)
> midm
[1] -0.3276434 -0.3230955 -0.3230955 -0.3230955 -0.3230955 -0.3269865 -0.3230955
[8] -0.3230955
> postscript(file="/var/wessaorg/rcomp/tmp/1792s1323518675.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/26tei1323518675.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/31wmt1323518675.tab") 
> 
> try(system("convert tmp/1792s1323518675.ps tmp/1792s1323518675.png",intern=TRUE))
character(0)
> try(system("convert tmp/26tei1323518675.ps tmp/26tei1323518675.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.652   0.140   1.802