Central tendency residuals: Dow Jones

*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 14:13:09 -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/t12292892495r3471go4dg8lxy.htm/, Retrieved Sun, 14 Dec 2008 22:14:11 +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/t12292892495r3471go4dg8lxy.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:

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Dataseries X:

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10.9678643829390 -527.941891732963 314.477803317794 -34.8206074871487 15.8868251444201 92.0121581344447 -739.165333715378 272.926305216330 308.006853284813 169.137257333146 -356.627822228997 -80.1398646279285 -1252.13402177254 374.034728260052 473.657389767743 179.546464104151 -94.2377996549658 -22.8257762393569 613.23098305044 -415.297145841570 -49.3545926875777 -572.818819385693 -785.420384864605 203.763779297073 -535.338794944188 -31.7870516461517 610.440315583619 -205.890149025499 -34.7802419865766 -550.009864591868 147.427229465278 347.480445842156 233.817027204646 430.213437584776 -16.7661383856866 121.72099342175 187.686269441698 157.875045166094 50.5407762573868 350.229292226122 359.611057100312 -2.39451452204958 -287.357251730726 137.450031041808 -340.014584492328 322.051962365935 -254.687098898155 -86.5260507905678 190.154869378788 -229.437320903528 441.400606381087 198.486809659575 -174.148319855576 204.8794816308 -70.0886350945511 -392.447145188338 155.396617898537 94.9901024988503 41.8884734495605 -0.153108620250350 -23.0986284581886 -204.884634826047 402.997312018986 75.4532463126234 24.2621947786756 91.832988388378 159.263451618912 62.1716287046438 85.4937017286156 -351.181984595320 90.6338341271548 214.468209269660 242.299861654394 387.002449348682 155.903230411013 158.288157865942 105.638962953013 97.7649863285405 -381.207103358456 542.146681541037 578.088024705992 -28.0626042491294 181.914677381284 -463.293407921557 384.728733477748 294.636515507867 -753.596181321631 314.263786350200 -900.624041336972 15.2107239480119 -207.439054699849 497.495304468926 84.608962989074 -779.803334669157 -617.931948820686 321.415015811461 -448.748865223051 -1868.20304615593 -269.69190087939

Output produced by software:

Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 1 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean -20.8182340489613 40.6564778672295 -0.512052079792714 Geometric Mean NaN Harmonic Mean -14.6126167373250 Quadratic Mean 403.016649458347 Winsorized Mean ( 1 / 33 ) -14.6235031710162 38.1667224924166 -0.3831479942749 Winsorized Mean ( 2 / 33 ) -8.17587307893654 35.9761094223529 -0.227258400372127 Winsorized Mean ( 3 / 33 ) -5.77398479689375 34.9587063045552 -0.165165860160603 Winsorized Mean ( 4 / 33 ) -7.35112931716296 34.6285461240991 -0.212285242667092 Winsorized Mean ( 5 / 33 ) -7.23147079967089 34.1542555081019 -0.211729715436352 Winsorized Mean ( 6 / 33 ) -8.31183054393774 33.6862830307809 -0.246742287842882 Winsorized Mean ( 7 / 33 ) -0.530784961223934 31.7762051319682 -0.0167038499096905 Winsorized Mean ( 8 / 33 ) 0.915437573661161 30.7689473801145 0.0297519951642153 Winsorized Mean ( 9 / 33 ) 1.53490049398125 30.1866447089396 0.0508470056470602 Winsorized Mean ( 10 / 33 ) 2.78715845122832 29.8823925527909 0.093270926894641 Winsorized Mean ( 11 / 33 ) 2.42081378384265 29.5780297010401 0.0818449980715764 Winsorized Mean ( 12 / 33 ) 8.50866986283248 27.9612667292244 0.304302016973338 Winsorized Mean ( 13 / 33 ) 9.18661038521741 27.4774853147284 0.334332282594042 Winsorized Mean ( 14 / 33 ) 13.5284308091084 26.6370050254210 0.507881077328235 Winsorized Mean ( 15 / 33 ) 13.1377515935040 25.5886370635221 0.513421311220697 Winsorized Mean ( 16 / 33 ) 14.8513831531659 25.2838330430452 0.587386537788069 Winsorized Mean ( 17 / 33 ) 17.8808292825443 24.469441142723 0.730741220375683 Winsorized Mean ( 18 / 33 ) 18.8320694036503 24.3104117890084 0.774650366562899 Winsorized Mean ( 19 / 33 ) 19.7744822694533 23.8303097761358 0.829803827781371 Winsorized Mean ( 20 / 33 ) 27.7112489330202 21.8935375340960 1.26572733574298 Winsorized Mean ( 21 / 33 ) 26.8532484457048 20.7806205626770 1.29222553122088 Winsorized Mean ( 22 / 33 ) 23.3817725388824 19.4933492661122 1.19947435505760 Winsorized Mean ( 23 / 33 ) 27.2771230594098 18.4234522415313 1.48056524378857 Winsorized Mean ( 24 / 33 ) 27.9194135487899 17.1415176003367 1.62875972826593 Winsorized Mean ( 25 / 33 ) 25.889155476944 16.8206836821466 1.53912623090479 Winsorized Mean ( 26 / 33 ) 25.8602171790536 16.7517753839967 1.54372993824632 Winsorized Mean ( 27 / 33 ) 32.8036749971371 15.4316867555843 2.12573489319088 Winsorized Mean ( 28 / 33 ) 53.0481218431477 12.2131492913649 4.34352521021375 Winsorized Mean ( 29 / 33 ) 54.583993751147 11.8540869142158 4.60465611110781 Winsorized Mean ( 30 / 33 ) 54.770234388185 11.4203450460495 4.79584760069319 Winsorized Mean ( 31 / 33 ) 57.1760273573121 10.9597556393612 5.21690713175833 Winsorized Mean ( 32 / 33 ) 60.513347966918 9.7963696562005 6.17711969746025 Winsorized Mean ( 33 / 33 ) 62.066741128983 8.8789350296807 6.99033621954715 Trimmed Mean ( 1 / 33 ) -8.30961966743998 36.2060357666546 -0.229509237658464 Trimmed Mean ( 2 / 33 ) -1.72988843739745 33.9171367196102 -0.0510033748337388 Trimmed Mean ( 3 / 33 ) 1.70103887180885 32.661883624284 0.0520802440966427 Trimmed Mean ( 4 / 33 ) 4.41176174067902 31.6714260582122 0.139297855820265 Trimmed Mean ( 5 / 33 ) 7.68290279328114 30.6470522154766 0.250689780513420 Trimmed Mean ( 6 / 33 ) 11.0772085075392 29.6068451691873 0.374143494325007 Trimmed Mean ( 7 / 33 ) 14.8409631469435 28.5239474685429 0.520298362045106 Trimmed Mean ( 8 / 33 ) 17.4602455268206 27.7358715496419 0.62951854588633 Trimmed Mean ( 9 / 33 ) 19.9879245196644 27.0405623111424 0.739183020296443 Trimmed Mean ( 10 / 33 ) 22.5573329283038 26.3487383120127 0.856106757795673 Trimmed Mean ( 11 / 33 ) 25.0992125039278 25.5997500040344 0.980447562963402 Trimmed Mean ( 12 / 33 ) 27.8206203503381 24.7762088160403 1.12287640764178 Trimmed Mean ( 13 / 33 ) 30.0031353026931 24.1101144938626 1.24442110427683 Trimmed Mean ( 14 / 33 ) 32.2358936632891 23.4078443746882 1.37714063487824 Trimmed Mean ( 15 / 33 ) 34.153118117289 22.7259869247288 1.50282221979658 Trimmed Mean ( 16 / 33 ) 36.2232885509753 22.0916578546394 1.63968176536684 Trimmed Mean ( 17 / 33 ) 38.2577295455745 21.3840081684739 1.78908131928126 Trimmed Mean ( 18 / 33 ) 40.1413085614848 20.6760527363735 1.94143964872307 Trimmed Mean ( 19 / 33 ) 42.0626334035846 19.84440481397 2.11962181773139 Trimmed Mean ( 20 / 33 ) 44.0309893021386 18.9154471743963 2.32777945433605 Trimmed Mean ( 21 / 33 ) 45.448229913141 18.1510282704522 2.50389285036405 Trimmed Mean ( 22 / 33 ) 47.0420854674927 17.4119861888162 2.70170702855875 Trimmed Mean ( 23 / 33 ) 49.0509799614313 16.7264389405140 2.93254171649306 Trimmed Mean ( 24 / 33 ) 50.8886712089165 16.0781184032849 3.16508872073735 Trimmed Mean ( 25 / 33 ) 52.8223076956108 15.5061340622688 3.40654269358754 Trimmed Mean ( 26 / 33 ) 55.0915690314815 14.8258435500269 3.71591463552045 Trimmed Mean ( 27 / 33 ) 55.0915690314815 13.9489225661201 3.9495214609113 Trimmed Mean ( 28 / 33 ) 59.6764211675489 13.1334347023479 4.54385486508571 Trimmed Mean ( 29 / 33 ) 60.24802537758 12.8496015545772 4.68870767094866 Trimmed Mean ( 30 / 33 ) 60.74381594435 12.5385070734847 4.84458122393258 Trimmed Mean ( 31 / 33 ) 61.2765948398999 12.2060110753646 5.02019820083358 Trimmed Mean ( 32 / 33 ) 61.6507480019056 11.8534754540841 5.20106936068812 Trimmed Mean ( 33 / 33 ) 61.7573792551857 11.6500787257583 5.30102677492129 Median 75.4532463126234 Midrange -627.486031552745 Midmean - Weighted Average at Xnp 47.6170804477016 Midmean - Weighted Average at X(n+1)p 50.8886712089165 Midmean - Empirical Distribution Function 50.8886712089165 Midmean - Empirical Distribution Function - Averaging 50.8886712089165 Midmean - Empirical Distribution Function - Interpolation 52.8223076956108 Midmean - Closest Observation 47.6170804477016 Midmean - True Basic - Statistics Graphics Toolkit 50.8886712089165 Midmean - MS Excel (old versions) 50.8886712089165 Number of observations 99

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/14/t12292892495r3471go4dg8lxy/1cfif1229289187.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/14/t12292892495r3471go4dg8lxy/1cfif1229289187.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/14/t12292892495r3471go4dg8lxy/2drjn1229289187.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/14/t12292892495r3471go4dg8lxy/2drjn1229289187.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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