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Robustness of Central Tendency

*The author of this computation has been verified*
R Software Module: rwasp_centraltendency.wasp (opens new window with default values)
Title produced by software: Central Tendency
Date of computation: Sun, 14 Dec 2008 03:59:53 -0700
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2008/Dec/14/t12292527923bs5z5ifgmkpnja.htm/, Retrieved Sun, 14 Dec 2008 12:06:32 +0100
 
BibTeX entries for LaTeX users:
@Manual{KEY,
    author = {{YOUR NAME}},
    publisher = {Office for Research Development and Education},
    title = {Statistical Computations at FreeStatistics.org, URL http://www.freestatistics.org/blog/date/2008/Dec/14/t12292527923bs5z5ifgmkpnja.htm/},
    year = {2008},
}
@Manual{R,
    title = {R: A Language and Environment for Statistical Computing},
    author = {{R Development Core Team}},
    organization = {R Foundation for Statistical Computing},
    address = {Vienna, Austria},
    year = {2008},
    note = {{ISBN} 3-900051-07-0},
    url = {http://www.R-project.org},
}
 
Original text written by user:
 
IsPrivate?
No (this computation is public)
 
User-defined keywords:
Paper Brutoschuld van de Belgische Schatkist
 
Dataseries X:
» Textbox « » Textfile « » CSV «
205597 205471 211064 212856 217036 219302 219759 221388 220834 221788 222358 222972 224164 224915 226294 224690 227021 229284 229189 230032 229389 231053 232560 232681 231555 231428 232141 234939 235424 235471 236355 238693 236958 237060 239282 238252 241552 236230 238909 240723 242120 242100 243276 244677 243494 244902 245247 245578 243052 238121 241863 241203 243634 242351 245180 246126 244424 245166 247258 245094 246020 243082 245555 243685 247277 245029 246169 246778 244577 246048 245775 245328 245477 241903 243219 248088 248521 247389 249057 248916 249193 250768 253106 249829 249447 246755 250785 250140 255755 254671 253919 253741 252729 253810 256653 255231 258405 251061 254811 254895 258325 257608 258759 258621 257852 260560 262358 260812 261165 257164 260720 259581 264743 261845 262262 261631 258953 259966 262850 262204 263418 262752 266433 267722 266003 262971 265521 264676 270223 269508 268457 265814 266680 263018 269285 269829 270911 266844 271244 269907 271296 270157 271322 267179 264101 265518 269419 268714 272482 268351 268175 270674 272764 272599 270333 270846 270491 269160 274027 273784 276663 274525 271344 271115 270798 273911 273985 271917 273338 270601 273547 275363 281229 277793 279913 282500 280041 282166 290304 283519 287816 285226 287595 289741 289148 288301 290155 289648 288225 289351 294735 305333
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24


Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean254924.8177083331386.87074444092183.812960746461
Geometric Mean254195.097771385
Harmonic Mean253455.690995277
Quadratic Mean255644.350772373
Winsorized Mean ( 1 / 64 )254870.2760416671377.31001994617185.049315223618
Winsorized Mean ( 2 / 64 )254881.0677083331360.52699053541187.339956856004
Winsorized Mean ( 3 / 64 )254906.7395833331355.57527285655188.043220238282
Winsorized Mean ( 4 / 64 )254985.1979166671340.87601070013190.163144005782
Winsorized Mean ( 5 / 64 )255041.7864583331332.02942267056191.468583289252
Winsorized Mean ( 6 / 64 )255046.7864583331328.77500902263191.941287822632
Winsorized Mean ( 7 / 64 )255078.5781251322.39394984436192.891519319959
Winsorized Mean ( 8 / 64 )255066.3697916671314.56492448395194.031017442366
Winsorized Mean ( 9 / 64 )255081.5572916671311.59002691643194.482690518292
Winsorized Mean ( 10 / 64 )255089.9427083331304.85997432071195.492196655912
Winsorized Mean ( 11 / 64 )255112.4583333331298.61044690614196.450335773228
Winsorized Mean ( 12 / 64 )255038.8958333331270.12933423526200.797579395244
Winsorized Mean ( 13 / 64 )254958.9322916671251.51039318203.720986802062
Winsorized Mean ( 14 / 64 )254901.0364583331240.66748072989205.454757553873
Winsorized Mean ( 15 / 64 )254982.6770833331224.20419388346208.284433558807
Winsorized Mean ( 16 / 64 )254965.1770833331207.83385378365211.092921666860
Winsorized Mean ( 17 / 64 )255051.9479166671173.26874190244217.385786229252
Winsorized Mean ( 18 / 64 )255048.8541666671170.90564088204217.821868186183
Winsorized Mean ( 19 / 64 )254849.4531251147.04926540968222.178297663595
Winsorized Mean ( 20 / 64 )254798.7239583331127.16220762518226.053288723340
Winsorized Mean ( 21 / 64 )254768.2083333331100.24571198261231.555738467046
Winsorized Mean ( 22 / 64 )254715.156251086.11884091832234.518679405872
Winsorized Mean ( 23 / 64 )254670.7135416671078.76088418405236.077074424416
Winsorized Mean ( 24 / 64 )254738.7135416671070.10864937500238.049392171951
Winsorized Mean ( 25 / 64 )254783.6354166671063.19983807504239.638519770622
Winsorized Mean ( 26 / 64 )254782.8229166671059.79157164867240.408425328682
Winsorized Mean ( 27 / 64 )255067.0260416671022.94293207363249.346291023894
Winsorized Mean ( 28 / 64 )255107.2760416671012.82355459767251.877313559323
Winsorized Mean ( 29 / 64 )255027.6770833331004.00552696037254.010232249847
Winsorized Mean ( 30 / 64 )255120.489583333989.647194145632257.789332493971
Winsorized Mean ( 31 / 64 )255121.78125985.888825504531258.773377535181
Winsorized Mean ( 32 / 64 )255128.114583333967.318577290092263.747766840233
Winsorized Mean ( 33 / 64 )255047.161458333956.727050073278266.582994009418
Winsorized Mean ( 34 / 64 )255231.151041667938.158326253853272.055519733888
Winsorized Mean ( 35 / 64 )255250.291666667935.456629009325272.861705985219
Winsorized Mean ( 36 / 64 )255323.229166667926.762584236846275.50014805239
Winsorized Mean ( 37 / 64 )255339.994791667920.629385472678277.353730850735
Winsorized Mean ( 38 / 64 )255373.442708333910.147910959293280.584550745351
Winsorized Mean ( 39 / 64 )255652.942708333882.442838536591289.710484967274
Winsorized Mean ( 40 / 64 )255742.942708333872.74992579975293.031182413429
Winsorized Mean ( 41 / 64 )255790.989583333863.893959546825296.090725900566
Winsorized Mean ( 42 / 64 )255843.052083333856.611594575098298.668677500493
Winsorized Mean ( 43 / 64 )255827.375853.627443379703299.694412338856
Winsorized Mean ( 44 / 64 )255836.3125846.5304397211302.217499212773
Winsorized Mean ( 45 / 64 )255815.21875843.824050444748303.161800869707
Winsorized Mean ( 46 / 64 )255854.75837.723742318785305.416615377051
Winsorized Mean ( 47 / 64 )255965.151041667817.922893988131312.945331305741
Winsorized Mean ( 48 / 64 )255953.151041667815.564443293337313.835593430361
Winsorized Mean ( 49 / 64 )255906.192708333805.407550715477317.735030520885
Winsorized Mean ( 50 / 64 )255897.859375802.136612051606319.020295957438
Winsorized Mean ( 51 / 64 )255920.171875794.241086512655322.219759492286
Winsorized Mean ( 52 / 64 )255924.234375788.160778699084324.710695192701
Winsorized Mean ( 53 / 64 )255815.197916667776.242006259534329.555983641441
Winsorized Mean ( 54 / 64 )255950.760416667753.123014378618339.852528113013
Winsorized Mean ( 55 / 64 )255964.223958333746.979829922702342.665509435269
Winsorized Mean ( 56 / 64 )255942.057291667740.204654379901345.772018288752
Winsorized Mean ( 57 / 64 )255874.369791667723.305415365347353.757022076798
Winsorized Mean ( 58 / 64 )255748.703125706.273657152123362.109927979255
Winsorized Mean ( 59 / 64 )255665.734375695.996150421022367.337856998696
Winsorized Mean ( 60 / 64 )255636.984375689.905261997688370.539258730653
Winsorized Mean ( 61 / 64 )255562.958333333682.993755298775374.180519734822
Winsorized Mean ( 62 / 64 )255445.739583333669.754999131607381.401766189935
Winsorized Mean ( 63 / 64 )255410.302083333662.528343562071385.508491169034
Winsorized Mean ( 64 / 64 )255362.302083333650.566736218822392.522838729094
Trimmed Mean ( 1 / 64 )254919.7947368421351.05844346390188.681545176734
Trimmed Mean ( 2 / 64 )254970.3670212771322.95273049175192.728251845024
Trimmed Mean ( 3 / 64 )255016.4569892471302.24070257100195.828971161607
Trimmed Mean ( 4 / 64 )255054.6195652171282.00359088326198.950004024163
Trimmed Mean ( 5 / 64 )255072.9285714291264.73380489084201.681118655197
Trimmed Mean ( 6 / 64 )255079.5722222221248.43074528077204.320162080641
Trimmed Mean ( 7 / 64 )255085.4662921351231.67512680373207.104504053839
Trimmed Mean ( 8 / 64 )255086.5397727271214.92245971002209.96116890753
Trimmed Mean ( 9 / 64 )255089.3218390801198.28589764079212.878514502513
Trimmed Mean ( 10 / 64 )255090.2848837211180.90602295657216.012349776204
Trimmed Mean ( 11 / 64 )255090.3235294121163.21695862679219.297287266644
Trimmed Mean ( 12 / 64 )255088.0238095241145.05522520677222.773555540485
Trimmed Mean ( 13 / 64 )255092.7590361451129.13988642206225.917764577838
Trimmed Mean ( 14 / 64 )255104.810975611114.24109999001228.949381761181
Trimmed Mean ( 15 / 64 )255122.0617283951099.43305752501232.048745471338
Trimmed Mean ( 16 / 64 )255133.21251085.28329639888235.084436797809
Trimmed Mean ( 17 / 64 )255145.9746835441071.74189741120238.066623409844
Trimmed Mean ( 18 / 64 )255152.7820512821060.59971335473240.574062804731
Trimmed Mean ( 19 / 64 )255159.9805194811048.78717237193243.290523798468
Trimmed Mean ( 20 / 64 )255180.6251038.23444601127245.783239017318
Trimmed Mean ( 21 / 64 )255205.0666666671028.59848027143248.109511691405
Trimmed Mean ( 22 / 64 )255232.0540540541020.49369830822250.106447964527
Trimmed Mean ( 23 / 64 )255262.9520547951012.85709723401252.022672055008
Trimmed Mean ( 24 / 64 )255297.2847222221005.12340361475253.995960898026
Trimmed Mean ( 25 / 64 )255328.753521127997.398422268976255.994743745715
Trimmed Mean ( 26 / 64 )255358.657142857989.516391310052258.064100186132
Trimmed Mean ( 27 / 64 )255389.471014493981.156867264164260.294229735776
Trimmed Mean ( 28 / 64 )255406.330882353974.96606320778261.964329344992
Trimmed Mean ( 29 / 64 )255421.634328358968.919721911953263.614857404635
Trimmed Mean ( 30 / 64 )255441.393939394962.894560251112265.284907075161
Trimmed Mean ( 31 / 64 )255457.192307692957.31997033012266.846195864483
Trimmed Mean ( 32 / 64 )255473.421875951.399205333712268.523896638520
Trimmed Mean ( 33 / 64 )255489.865079365946.205188147155270.015286620507
Trimmed Mean ( 34 / 64 )255510.637096774941.160897134561271.484544114292
Trimmed Mean ( 35 / 64 )255523.573770492936.890738587888272.735723864263
Trimmed Mean ( 36 / 64 )255536.066666667932.244532840108274.108410041483
Trimmed Mean ( 37 / 64 )255545.686440678927.629773858545275.482410808912
Trimmed Mean ( 38 / 64 )255554.887931034922.841452575921276.921769408717
Trimmed Mean ( 39 / 64 )255562.929824561918.178994025965278.336720277152
Trimmed Mean ( 40 / 64 )255558.973214286914.91321678632279.325916956309
Trimmed Mean ( 41 / 64 )255550.945454545911.792721023344280.273070361573
Trimmed Mean ( 42 / 64 )255540.537037037908.756533538664281.198019057945
Trimmed Mean ( 43 / 64 )255527.490566038905.681298283369282.138420049487
Trimmed Mean ( 44 / 64 )255514.615384615902.238098461737283.200871056380
Trimmed Mean ( 45 / 64 )255500.852941176898.691429284985284.303204209322
Trimmed Mean ( 46 / 64 )255487.44894.68493402748285.561352698661
Trimmed Mean ( 47 / 64 )255471.795918367890.418121849922286.91217041675
Trimmed Mean ( 48 / 64 )255450.802083333886.924412390263288.018684021666
Trimmed Mean ( 49 / 64 )255429.425531915882.890291007333289.310493198971
Trimmed Mean ( 50 / 64 )255409.119565217878.895256374495290.602455426598
Trimmed Mean ( 51 / 64 )255388.266666667874.345159178157292.090902529522
Trimmed Mean ( 52 / 64 )255365.511363636869.550661505312293.675253977225
Trimmed Mean ( 53 / 64 )255341.523255814864.315861243083295.426168494206
Trimmed Mean ( 54 / 64 )255321.095238095859.136682017224297.183324356038
Trimmed Mean ( 55 / 64 )255293.792682927854.939754932609298.610271905125
Trimmed Mean ( 56 / 64 )255264.5375850.295466506759300.206866383394
Trimmed Mean ( 57 / 64 )255234.756410256845.206447043468301.979187810348
Trimmed Mean ( 58 / 64 )255206.407894737840.610856456275303.596373916225
Trimmed Mean ( 59 / 64 )255182.148648649836.594260418476305.024981310538
Trimmed Mean ( 60 / 64 )255160.291666667832.511523048427306.494606503872
Trimmed Mean ( 61 / 64 )255138.5827.87598233824308.184444823959
Trimmed Mean ( 62 / 64 )255118.852941176822.693804943337310.101828175001
Trimmed Mean ( 63 / 64 )255103.515151515817.592331560074312.017989044423
Trimmed Mean ( 64 / 64 )255088.90625811.834684171589314.212870210513
Median255063
Midrange255402
Midmean - Weighted Average at Xnp255322.979381443
Midmean - Weighted Average at X(n+1)p255450.802083333
Midmean - Empirical Distribution Function255322.979381443
Midmean - Empirical Distribution Function - Averaging255450.802083333
Midmean - Empirical Distribution Function - Interpolation255450.802083333
Midmean - Closest Observation255322.979381443
Midmean - True Basic - Statistics Graphics Toolkit255450.802083333
Midmean - MS Excel (old versions)255471.795918367
Number of observations192
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/14/t12292527923bs5z5ifgmkpnja/1oxgd1229252388.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/14/t12292527923bs5z5ifgmkpnja/1oxgd1229252388.ps (open in new window)


http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/14/t12292527923bs5z5ifgmkpnja/2j9dy1229252388.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/14/t12292527923bs5z5ifgmkpnja/2j9dy1229252388.ps (open in new window)


 
Parameters (Session):
 
Parameters (R input):
 
R code (references can be found in the software module):
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))
sqrtn <- sqrt(length(x))
(armse <- sd(x) / sqrtn)
(armose <- arm / armse)
(geo <- geomean(x))
(har <- harmean(x))
(qua <- quamean(x))
(win <- winmean(x))
(tri <- trimean(x))
(midr <- midrange(x))
midm <- array(NA,dim=8)
for (j in 1:8) midm[j] <- midmean(x,j)
midm
bitmap(file='test1.png')
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()
bitmap(file='test2.png')
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()
load(file='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='mytable.tab')
 




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Software written by Ed van Stee & Patrick Wessa


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