R version 2.12.0 (2010-10-15)
Copyright (C) 2010 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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'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(8.6658
+ ,8.756
+ ,8.8178
+ ,8.8595
+ ,8.8762
+ ,8.968
+ ,9.0638
+ ,9.0789
+ ,9.0529
+ ,8.9548
+ ,9.0355
+ ,9.053
+ ,9.1
+ ,9.0772
+ ,9.1346
+ ,9.2651
+ ,9.2939
+ ,9.3752
+ ,9.4915
+ ,9.3559
+ ,9.3608
+ ,9.3325
+ ,9.2437
+ ,9.2667
+ ,9.2212
+ ,9.2691
+ ,9.342
+ ,9.2787
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+ ,9.2202
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+ ,9.3018
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+ ,9.2713
+ ,9.2205
+ ,9.1703
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+ ,9.0055
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+ ,9.1054
+ ,9.2285
+ ,9.1961
+ ,9.2486
+ ,9.3245
+ ,9.3898
+ ,9.3672
+ ,9.355
+ ,9.3953
+ ,9.3231
+ ,9.29
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+ ,9.8097
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+ ,9.8863
+ ,9.9174
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+ ,9.8598
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+ ,9.7861
+ ,9.8569
+ ,9.8386
+ ,9.831
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+ ,9.7498
+ ,9.8105
+ ,9.7893
+ ,9.7943
+ ,9.9416
+ ,9.9286
+ ,10.0013
+ ,10.0755
+ ,10.0556
+ ,10.083
+ ,10.0869
+ ,10.0982
+ ,10.2869
+ ,10.3224
+ ,10.3009
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+ ,10.1866
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+ ,10.0773
+ ,10.0085
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+ ,10.091
+ ,10.0902
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+ ,10.0141
+ ,9.9777
+ ,9.9436
+ ,9.9662
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+ ,9.9168
+ ,9.8814
+ ,9.786
+ ,9.7409
+ ,9.7915
+ ,9.7137
+ ,9.777
+ ,9.7486
+ ,9.8108
+ ,9.7479
+ ,9.748
+ ,9.7859
+ ,9.7845
+ ,9.7891
+ ,9.7305
+ ,9.6443
+ ,9.6365
+ ,9.6203
+ ,9.7688
+ ,9.7674
+ ,9.6853
+ ,9.6825
+ ,9.7062
+ ,9.8084
+ ,9.8164
+ ,9.8433
+ ,9.8246
+ ,9.7701
+ ,9.6592
+ ,9.6014
+ ,9.635
+ ,9.7197
+ ,9.7472
+ ,9.7185
+ ,9.7198
+ ,9.6933
+ ,9.7153
+ ,9.7118
+ ,9.6259
+ ,9.6526
+ ,9.625
+ ,9.5599
+ ,9.5487
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+ ,9.4984
+ ,9.5788
+ ,9.4979
+ ,9.5714
+ ,9.5974
+ ,9.6319
+ ,9.6545
+ ,9.607
+ ,9.6329
+ ,9.5276
+ ,9.5857
+ ,9.5537
+ ,9.4728
+ ,9.5242
+ ,9.5139
+ ,9.463
+ ,9.4926
+ ,9.4684
+ ,9.5701
+ ,9.5475
+ ,9.6365
+ ,9.5415
+ ,9.4803
+ ,9.6871
+ ,9.6313
+ ,9.7044
+ ,9.7261
+ ,9.7073
+ ,9.6263
+ ,9.461
+ ,9.4917
+ ,9.5
+ ,9.5601
+ ,9.5334
+ ,9.3983
+ ,9.3434
+ ,9.2896
+ ,9.2124
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+ ,9.0221
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+ ,8.8692
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+ ,9.0339
+ ,8.913
+ ,8.8428
+ ,8.8354
+ ,8.8604
+ ,8.922
+ ,9.0163
+ ,9.0001
+ ,9.0702
+ ,9.0717
+ ,9.0446
+ ,9.0622
+ ,9.2242
+ ,9.1757
+ ,9.1533
+ ,9.0527
+ ,9.0942
+ ,9.0893
+ ,9.0838
+ ,9.2191
+ ,9.2176
+ ,9.2247
+ ,9.2623
+ ,9.2509
+ ,9.3352
+ ,8.974
+ ,8.8487
+ ,8.9183
+ ,8.8244
+ ,8.7414
+ ,8.7461
+ ,8.7451
+ ,8.5945
+ ,8.6581
+ ,8.5885
+ ,8.5915
+ ,8.6303
+ ,8.623
+ ,8.6482
+ ,8.7429
+ ,8.7485
+ ,8.7264
+ ,8.7487
+ ,8.6087
+ ,8.6844
+ ,8.6131
+ ,8.641
+ ,8.7236
+ ,8.7626
+ ,8.7703
+ ,8.8409
+ ,8.8598
+ ,8.8894
+ ,8.7453
+ ,8.7708
+ ,8.7598
+ ,8.7891
+ ,8.7389
+ ,8.7636
+ ,8.9653
+ ,9.0672
+ ,9.0084
+ ,8.8826
+ ,8.7492
+ ,8.8773
+ ,8.8276
+ ,8.8422
+ ,9.0111
+ ,9.0732
+ ,8.9453
+ ,9.004
+ ,9.0634
+ ,9.1575
+ ,9.3538
+ ,9.3068
+ ,9.2908
+ ,9.1138
+ ,9.2781
+ ,9.4608)
> 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: Wessa, P., (2007), Central Tendency (v1.0.2) 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
> #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] 9.269986
> sqrtn <- sqrt(length(x))
> (armse <- sd(x) / sqrtn)
[1] 0.02393877
> (armose <- arm / armse)
[1] 387.2373
> (geo <- geomean(x))
[1] 9.254852
> (har <- harmean(x))
[1] 9.23974
> (qua <- quamean(x))
[1] 9.28512
> (win <- winmean(x))
           [,1]       [,2]
  [1,] 9.269973 0.02393204
  [2,] 9.270080 0.02391956
  [3,] 9.270198 0.02390031
  [4,] 9.270251 0.02389375
  [5,] 9.270747 0.02384864
  [6,] 9.270545 0.02381819
  [7,] 9.270582 0.02379662
  [8,] 9.270898 0.02377061
  [9,] 9.271166 0.02374381
 [10,] 9.271086 0.02371374
 [11,] 9.270822 0.02368154
 [12,] 9.270724 0.02366598
 [13,] 9.270782 0.02365964
 [14,] 9.270911 0.02363620
 [15,] 9.270822 0.02362846
 [16,] 9.271112 0.02360365
 [17,] 9.271029 0.02357975
 [18,] 9.270292 0.02349724
 [19,] 9.270312 0.02349391
 [20,] 9.270324 0.02349232
 [21,] 9.270610 0.02345341
 [22,] 9.269535 0.02335776
 [23,] 9.270233 0.02330293
 [24,] 9.270179 0.02327775
 [25,] 9.270790 0.02320379
 [26,] 9.270854 0.02319744
 [27,] 9.271305 0.02316060
 [28,] 9.271738 0.02312089
 [29,] 9.271892 0.02310785
 [30,] 9.271916 0.02308583
 [31,] 9.272819 0.02301841
 [32,] 9.272421 0.02274503
 [33,] 9.272085 0.02266386
 [34,] 9.272023 0.02260298
 [35,] 9.273042 0.02252185
 [36,] 9.272984 0.02250800
 [37,] 9.272969 0.02246045
 [38,] 9.273766 0.02239715
 [39,] 9.273559 0.02237390
 [40,] 9.273820 0.02234812
 [41,] 9.275816 0.02217713
 [42,] 9.276808 0.02210497
 [43,] 9.276677 0.02205620
 [44,] 9.276945 0.02203379
 [45,] 9.277697 0.02196257
 [46,] 9.277912 0.02193974
 [47,] 9.277510 0.02187310
 [48,] 9.276337 0.02178435
 [49,] 9.276856 0.02167104
 [50,] 9.276500 0.02160230
 [51,] 9.276676 0.02155323
 [52,] 9.275713 0.02147382
 [53,] 9.275238 0.02130675
 [54,] 9.275117 0.02127175
 [55,] 9.274848 0.02122439
 [56,] 9.275110 0.02118836
 [57,] 9.274472 0.02113260
 [58,] 9.274354 0.02112430
 [59,] 9.273789 0.02107201
 [60,] 9.272469 0.02086301
 [61,] 9.272506 0.02085420
 [62,] 9.271256 0.02074857
 [63,] 9.268562 0.02053946
 [64,] 9.269070 0.02047932
 [65,] 9.269931 0.02042114
 [66,] 9.269030 0.02034707
 [67,] 9.269248 0.02032142
 [68,] 9.268999 0.02025168
 [69,] 9.269125 0.02017584
 [70,] 9.269382 0.02013480
 [71,] 9.268876 0.02005543
 [72,] 9.269756 0.01999097
 [73,] 9.266708 0.01967397
 [74,] 9.266391 0.01962340
 [75,] 9.265979 0.01955497
 [76,] 9.263766 0.01927402
 [77,] 9.263671 0.01922367
 [78,] 9.261860 0.01906740
 [79,] 9.262037 0.01896442
 [80,] 9.262510 0.01886484
 [81,] 9.262444 0.01878873
 [82,] 9.261843 0.01869515
 [83,] 9.262536 0.01863784
 [84,] 9.261749 0.01853202
 [85,] 9.261264 0.01849000
 [86,] 9.261071 0.01845520
 [87,] 9.261709 0.01841131
 [88,] 9.262032 0.01837526
 [89,] 9.262431 0.01832383
 [90,] 9.260543 0.01819214
 [91,] 9.260450 0.01813160
 [92,] 9.260207 0.01808369
 [93,] 9.260112 0.01803994
 [94,] 9.260169 0.01803207
 [95,] 9.259627 0.01799511
 [96,] 9.259764 0.01798482
 [97,] 9.260061 0.01796523
 [98,] 9.259941 0.01793926
 [99,] 9.258469 0.01784695
[100,] 9.257166 0.01775793
[101,] 9.258297 0.01766073
[102,] 9.258297 0.01762671
[103,] 9.258570 0.01758394
[104,] 9.255668 0.01734499
[105,] 9.255668 0.01732016
[106,] 9.256272 0.01728015
[107,] 9.256991 0.01722852
[108,] 9.257057 0.01721962
[109,] 9.258700 0.01712268
[110,] 9.259126 0.01708022
[111,] 9.258922 0.01703184
[112,] 9.259561 0.01689036
[113,] 9.258456 0.01667843
[114,] 9.258851 0.01653927
[115,] 9.258593 0.01638561
[116,] 9.258924 0.01636429
[117,] 9.261093 0.01621026
[118,] 9.260444 0.01615932
[119,] 9.261025 0.01608299
[120,] 9.261074 0.01602777
[121,] 9.260483 0.01593545
[122,] 9.260483 0.01590463
[123,] 9.261760 0.01578308
[124,] 9.259185 0.01561073
[125,] 9.259006 0.01544383
[126,] 9.258878 0.01539928
[127,] 9.258309 0.01534982
[128,] 9.254164 0.01494675
[129,] 9.254978 0.01485807
[130,] 9.254369 0.01475404
[131,] 9.253916 0.01472306
[132,] 9.254131 0.01462815
[133,] 9.253752 0.01459827
[134,] 9.252878 0.01453216
[135,] 9.253153 0.01428141
[136,] 9.255092 0.01417534
[137,] 9.254981 0.01413563
[138,] 9.255880 0.01402217
[139,] 9.257522 0.01390231
[140,] 9.258577 0.01382676
[141,] 9.262684 0.01345137
[142,] 9.263985 0.01336996
[143,] 9.263839 0.01334933
[144,] 9.263546 0.01321603
[145,] 9.263989 0.01304641
[146,] 9.263513 0.01279362
[147,] 9.263932 0.01276206
[148,] 9.264294 0.01257231
[149,] 9.264810 0.01253898
[150,] 9.266490 0.01232818
[151,] 9.262954 0.01212873
[152,] 9.262737 0.01191354
[153,] 9.261490 0.01173422
[154,] 9.261365 0.01169767
[155,] 9.259060 0.01148415
[156,] 9.259124 0.01147418
[157,] 9.260147 0.01134072
[158,] 9.267259 0.01096153
[159,] 9.267324 0.01084686
[160,] 9.266965 0.01069534
[161,] 9.267064 0.01064952
[162,] 9.267624 0.01058034
[163,] 9.266927 0.01044999
> (tri <- trimean(x))
           [,1]       [,2]
  [1,] 9.269986 0.02383114
  [2,] 9.270112 0.02372773
  [3,] 9.270341 0.02362822
  [4,] 9.270341 0.02353294
  [5,] 9.270425 0.02343701
  [6,] 9.270359 0.02334835
  [7,] 9.270328 0.02326294
  [8,] 9.270328 0.02317874
  [9,] 9.270211 0.02309597
 [10,] 9.270101 0.02301441
 [11,] 9.269997 0.02293413
 [12,] 9.269919 0.02285512
 [13,] 9.269848 0.02277554
 [14,] 9.269771 0.02269444
 [15,] 9.269685 0.02261318
 [16,] 9.269685 0.02253037
 [17,] 9.269502 0.02244725
 [18,] 9.269405 0.02236363
 [19,] 9.269352 0.02228346
 [20,] 9.269297 0.02220133
 [21,] 9.269241 0.02211709
 [22,] 9.269169 0.02203292
 [23,] 9.269151 0.02195211
 [24,] 9.269099 0.02187220
 [25,] 9.269049 0.02179146
 [26,] 9.268971 0.02171244
 [27,] 9.268889 0.02163154
 [28,] 9.268789 0.02155024
 [29,] 9.268669 0.02146861
 [30,] 9.268542 0.02138529
 [31,] 9.268414 0.02130065
 [32,] 9.268414 0.02121670
 [33,] 9.268100 0.02114270
 [34,] 9.267960 0.02107013
 [35,] 9.267820 0.02099806
 [36,] 9.267645 0.02092728
 [37,] 9.267471 0.02085497
 [38,] 9.267295 0.02078246
 [39,] 9.267092 0.02071031
 [40,] 9.266894 0.02063693
 [41,] 9.266687 0.02056233
 [42,] 9.266418 0.02049201
 [43,] 9.266118 0.02042223
 [44,] 9.265819 0.02035213
 [45,] 9.265509 0.02028067
 [46,] 9.265176 0.02020957
 [47,] 9.264834 0.02013705
 [48,] 9.264498 0.02006466
 [49,] 9.264190 0.01999318
 [50,] 9.263865 0.01992339
 [51,] 9.263547 0.01985375
 [52,] 9.263220 0.01978355
 [53,] 9.262914 0.01971383
 [54,] 9.262615 0.01964750
 [55,] 9.262317 0.01958015
 [56,] 9.262022 0.01951215
 [57,] 9.261718 0.01944308
 [58,] 9.261425 0.01937355
 [59,] 9.261131 0.01930197
 [60,] 9.260847 0.01922971
 [61,] 9.260589 0.01916182
 [62,] 9.260328 0.01909189
 [63,] 9.260091 0.01902298
 [64,] 9.260091 0.01895840
 [65,] 9.259714 0.01889343
 [66,] 9.259499 0.01882797
 [67,] 9.259301 0.01876254
 [68,] 9.259095 0.01869556
 [69,] 9.258893 0.01862837
 [70,] 9.258685 0.01856110
 [71,] 9.258470 0.01849267
 [72,] 9.258263 0.01842422
 [73,] 9.258036 0.01835523
 [74,] 9.257866 0.01829347
 [75,] 9.257700 0.01823093
 [76,] 9.257540 0.01816811
 [77,] 9.257421 0.01811139
 [78,] 9.257302 0.01805397
 [79,] 9.257216 0.01799899
 [80,] 9.257125 0.01794486
 [81,] 9.257025 0.01789150
 [82,] 9.256924 0.01783822
 [83,] 9.256834 0.01778554
 [84,] 9.256729 0.01773235
 [85,] 9.256638 0.01768009
 [86,] 9.256554 0.01762688
 [87,] 9.256473 0.01757246
 [88,] 9.256379 0.01751705
 [89,] 9.256278 0.01746036
 [90,] 9.256169 0.01740280
 [91,] 9.256092 0.01734672
 [92,] 9.256015 0.01729003
 [93,] 9.255942 0.01723232
 [94,] 9.255869 0.01717342
 [95,] 9.255794 0.01711220
 [96,] 9.255728 0.01704944
 [97,] 9.255659 0.01698427
 [98,] 9.255583 0.01691685
 [99,] 9.255509 0.01684730
[100,] 9.255458 0.01677757
[101,] 9.255429 0.01670754
[102,] 9.255380 0.01663740
[103,] 9.255331 0.01656520
[104,] 9.255277 0.01649111
[105,] 9.255270 0.01642119
[106,] 9.255263 0.01634886
[107,] 9.255247 0.01627449
[108,] 9.255217 0.01619835
[109,] 9.255187 0.01611899
[110,] 9.255128 0.01603908
[111,] 9.255062 0.01595684
[112,] 9.254998 0.01587234
[113,] 9.254923 0.01578854
[114,] 9.254864 0.01570780
[115,] 9.254798 0.01562778
[116,] 9.254736 0.01554899
[117,] 9.254667 0.01546706
[118,] 9.254561 0.01538624
[119,] 9.254464 0.01530316
[120,] 9.254357 0.01521854
[121,] 9.254246 0.01513158
[122,] 9.254144 0.01504347
[123,] 9.254144 0.01495197
[124,] 9.253913 0.01486008
[125,] 9.253826 0.01476970
[126,] 9.253741 0.01468060
[127,] 9.253657 0.01458845
[128,] 9.253657 0.01449325
[129,] 9.253570 0.01440781
[130,] 9.253547 0.01432099
[131,] 9.253534 0.01423327
[132,] 9.253527 0.01414190
[133,] 9.253517 0.01404907
[134,] 9.253513 0.01395222
[135,] 9.253524 0.01385252
[136,] 9.253530 0.01375701
[137,] 9.253504 0.01366021
[138,] 9.253480 0.01355943
[139,] 9.253439 0.01345738
[140,] 9.253371 0.01335423
[141,] 9.253284 0.01324809
[142,] 9.253126 0.01315102
[143,] 9.252942 0.01305139
[144,] 9.252758 0.01294655
[145,] 9.252575 0.01284102
[146,] 9.252381 0.01273627
[147,] 9.252191 0.01263601
[148,] 9.251990 0.01253074
[149,] 9.251778 0.01242716
[150,] 9.251553 0.01231832
[151,] 9.251295 0.01221187
[152,] 9.251092 0.01210796
[153,] 9.250889 0.01200712
[154,] 9.250703 0.01190796
[155,] 9.250515 0.01180372
[156,] 9.250364 0.01170274
[157,] 9.250208 0.01159516
[158,] 9.250030 0.01148654
[159,] 9.249721 0.01138824
[160,] 9.249403 0.01128848
[161,] 9.249084 0.01118910
[162,] 9.248756 0.01108461
[163,] 9.248409 0.01097575
> (midr <- midrange(x))
[1] 9.2391
> midm <- array(NA,dim=8)
> for (j in 1:8) midm[j] <- midmean(x,j)
> midm
[1] 9.252306 9.254144 9.254144 9.254144 9.254040 9.252306 9.254144 9.254144
> postscript(file="/var/www/rcomp/tmp/1blzm1291669503.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/www/rcomp/tmp/24cyp1291669503.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/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/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/rcomp/tmp/3of761291669503.tab") 
> 
> try(system("convert tmp/1blzm1291669503.ps tmp/1blzm1291669503.png",intern=TRUE))
character(0)
> try(system("convert tmp/24cyp1291669503.ps tmp/24cyp1291669503.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  3.120   0.370   3.485