*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: Wed, 10 Dec 2008 13:54:53 -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/10/t1228942602osjpkwvznhwibeo.htm/, Retrieved Wed, 10 Dec 2008 20:56:45 +0000

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/10/t1228942602osjpkwvznhwibeo.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}, }

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2008-11-27 13:41:43 [a2386b643d711541400692649981f2dc]  [reply]  test Post a new message

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Dataseries X:

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1.10988636363636 1.08488636363637 0.797386363636364 0.759886363636359 0.44738636363636 0.184886363636360 0.172386363636364 -0.0651136363636372 -0.62761363636363 -1.17761363636364 -1.35032467532468 -1.33603896103896 3.00436688311689 3.27936688311688 3.59186688311688 4.15436688311688 3.54186688311688 3.67936688311688 1.76686688311689 1.52936688311688 1.46686688311688 1.71686688311688 1.84415584415585 1.45844155844156 -1.04994047619047 -1.17494047619048 -1.26244047619048 -1.39994047619048 -1.71244047619048 -1.77494047619049 -1.48744047619047 -1.22494047619047 -0.687440476190472 -0.237440476190477 0.389848484848482 0.204134199134194 -0.104247835497830 -0.0292478354978352 -0.0167478354978383 0.0457521645021657 0.0332521645021633 -0.0292478354978325 0.0582521645021616 -0.279247835497833 -0.641747835497837 -1.19174783549784 -1.06445887445888 -1.35017316017316 -2.15855519480519 -2.18355519480519 -2.17105519480519 -2.80855519480519 -2.32105519480519 -2.08355519480519 -1.49605519480520 -1.83355519480519 -2.3960551948052 -2.64605519480519 -2.31876623376623 -2.30448051948052 -3.01286255411256 -3.03786255411256 -3.12536255411256 -2.76286255411255 -1.87536255411255 -1.83786255411255 -1.55036255411256 -0.787862554112556 -0.750362554112555 -0.700362554112551 -0.37307359307359 0.141212121212125 -0.167169913419916 -0.492169913419909 -0.579669913419907 -0.417169913419911 -0.429669913419912 -0.19216991341991 0.395330086580084 0.55783008658009 1.39533008658009 2.54533008658009 2.87261904761905 3.18690476190476 2.37852272727272 2.55352272727272 2.76602272727273 2.42852272727272 2.31602272727273 2.05352272727273 2.14102272727273 2.10352272727272 2.24102272727272 1.69102272727273

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 'George Udny Yule' @ 72.249.76.132 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean -6.87787869654076e-17 0.188601844190909 -3.64677170896523e-16 Geometric Mean NaN Harmonic Mean -1.00290347272762 Quadratic Mean 1.81881031825633 Winsorized Mean ( 1 / 31 ) -0.00412234042553198 0.187304925867950 -0.0220087133663437 Winsorized Mean ( 2 / 31 ) -0.00545212765957454 0.186823000140466 -0.0291833856402866 Winsorized Mean ( 3 / 31 ) -0.000527424702956341 0.185398469002202 -0.00284481692753393 Winsorized Mean ( 4 / 31 ) -0.00975326977986528 0.182854567025526 -0.0533389454719157 Winsorized Mean ( 5 / 31 ) -0.0084583103067142 0.180921875893298 -0.0467511751409357 Winsorized Mean ( 6 / 31 ) -0.00415221746338742 0.176330635112561 -0.0235479073771658 Winsorized Mean ( 7 / 31 ) -0.00837812010684285 0.173748803984990 -0.048219728220786 Winsorized Mean ( 8 / 31 ) -0.0172553421755543 0.172123325168997 -0.100249876991467 Winsorized Mean ( 9 / 31 ) -0.0362333057013915 0.168474816222871 -0.215066598757760 Winsorized Mean ( 10 / 31 ) -0.0242404669798277 0.166502138031850 -0.145586520788044 Winsorized Mean ( 11 / 31 ) -0.0364466473243072 0.164059312720814 -0.222155309076114 Winsorized Mean ( 12 / 31 ) -0.0412338813668604 0.162810448065373 -0.253263115830894 Winsorized Mean ( 13 / 31 ) -0.0395051579626037 0.159997802918893 -0.246910627782995 Winsorized Mean ( 14 / 31 ) -0.0196679561573184 0.154092887540253 -0.127637014733601 Winsorized Mean ( 15 / 31 ) -0.0296413604126358 0.150826088594179 -0.196526746061755 Winsorized Mean ( 16 / 31 ) -0.0352911715943635 0.149747453094102 -0.235671264286454 Winsorized Mean ( 17 / 31 ) -0.033733190568299 0.147003223029183 -0.229472455591007 Winsorized Mean ( 18 / 31 ) -0.0618566362715293 0.139470412985886 -0.443510813134174 Winsorized Mean ( 19 / 31 ) -0.0447184420189737 0.133100295907144 -0.335975526682307 Winsorized Mean ( 20 / 31 ) -0.0438019825918779 0.130152043668289 -0.336544716143785 Winsorized Mean ( 21 / 31 ) -0.0476511121856845 0.129083140130136 -0.369150550084579 Winsorized Mean ( 22 / 31 ) -0.0650067352859922 0.121225021712665 -0.53624849364907 Winsorized Mean ( 23 / 31 ) -0.0681592520954241 0.117640506539792 -0.579385911368624 Winsorized Mean ( 24 / 31 ) -0.0702717141015007 0.117334380674452 -0.59890130835967 Winsorized Mean ( 25 / 31 ) -0.0832975845076896 0.114552219818791 -0.727158187239472 Winsorized Mean ( 26 / 31 ) -0.141893075895737 0.101413663904691 -1.39915145979825 Winsorized Mean ( 27 / 31 ) -0.138302650363817 0.0991866613067781 -1.39436743350051 Winsorized Mean ( 28 / 31 ) -0.214053778668142 0.0869527856658597 -2.46172422227740 Winsorized Mean ( 29 / 31 ) -0.221262376807592 0.0849836875278044 -2.60358644398904 Winsorized Mean ( 30 / 31 ) -0.284895286451137 0.0770754041575917 -3.69631907305511 Winsorized Mean ( 31 / 31 ) -0.284882794510457 0.0683348961077547 -4.1689211623478 Trimmed Mean ( 1 / 31 ) -0.0111848296630905 0.184155108638888 -0.0607359184643798 Trimmed Mean ( 2 / 31 ) -0.0185612073112072 0.180557694801176 -0.102799314820928 Trimmed Mean ( 3 / 31 ) -0.0185612073112072 0.176732103782526 -0.105024536651515 Trimmed Mean ( 4 / 31 ) -0.0346840078526123 0.172948423312814 -0.200545383347490 Trimmed Mean ( 5 / 31 ) -0.0416586786229641 0.169463303890000 -0.245827135826440 Trimmed Mean ( 6 / 31 ) -0.0416586786229641 0.165992006999525 -0.250967979579181 Trimmed Mean ( 7 / 31 ) -0.0581061282467531 0.163123672490764 -0.35620904899651 Trimmed Mean ( 8 / 31 ) -0.0666673604173603 0.160364623683066 -0.415723610895114 Trimmed Mean ( 9 / 31 ) -0.0743067185007975 0.157477181993344 -0.471857049765713 Trimmed Mean ( 10 / 31 ) -0.0796804434304433 0.15481495718257 -0.51468181679938 Trimmed Mean ( 11 / 31 ) -0.0869184403559404 0.152028934148189 -0.571723013404917 Trimmed Mean ( 12 / 31 ) -0.0869184403559404 0.149172243029748 -0.58267167262885 Trimmed Mean ( 13 / 31 ) -0.0990523936847466 0.145989295846763 -0.678490796946625 Trimmed Mean ( 14 / 31 ) -0.105576216712580 0.142674918648907 -0.739977409571064 Trimmed Mean ( 15 / 31 ) -0.114588913690476 0.139695618593324 -0.8202756453233 Trimmed Mean ( 16 / 31 ) -0.123175010473398 0.136649792001668 -0.901391862139784 Trimmed Mean ( 17 / 31 ) -0.131780303030303 0.133121886982477 -0.989922138405756 Trimmed Mean ( 18 / 31 ) -0.141127593670697 0.129278904257287 -1.09165214913819 Trimmed Mean ( 19 / 31 ) -0.148519925015461 0.125924966428176 -1.17943192067613 Trimmed Mean ( 20 / 31 ) -0.158030002405002 0.122860596147033 -1.28625456298357 Trimmed Mean ( 21 / 31 ) -0.168354458041958 0.119529642224663 -1.40847454161643 Trimmed Mean ( 22 / 31 ) -0.179160281385281 0.115505815156612 -1.55109317346803 Trimmed Mean ( 23 / 31 ) -0.189321676587301 0.111947180200143 -1.69116967706401 Trimmed Mean ( 24 / 31 ) -0.189321676587301 0.108071274995833 -1.75182236532882 Trimmed Mean ( 25 / 31 ) -0.211642070051161 0.103063715623701 -2.0535070831707 Trimmed Mean ( 26 / 31 ) -0.223131957328386 0.0971274303254198 -2.29731144518902 Trimmed Mean ( 27 / 31 ) -0.230474702380952 0.09263119483082 -2.48808949082312 Trimmed Mean ( 28 / 31 ) -0.238919315333789 0.0870889774608222 -2.74339327776892 Trimmed Mean ( 29 / 31 ) -0.241238125300625 0.0830078774060632 -2.90620761353192 Trimmed Mean ( 30 / 31 ) -0.243142507002801 0.0778648623075737 -3.12262167808586 Trimmed Mean ( 31 / 31 ) -0.243142507002801 0.073040778395035 -3.32885974582287 Median -0.179669913419913 Midrange 0.51450216450216 Midmean - Weighted Average at Xnp -0.224559731049093 Midmean - Weighted Average at X(n+1)p -0.189321676587302 Midmean - Empirical Distribution Function -0.189321676587302 Midmean - Empirical Distribution Function - Averaging -0.189321676587302 Midmean - Empirical Distribution Function - Interpolation -0.20008658008658 Midmean - Closest Observation -0.189321676587302 Midmean - True Basic - Statistics Graphics Toolkit -0.189321676587302 Midmean - MS Excel (old versions) -0.189321676587302 Number of observations 94

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/10/t1228942602osjpkwvznhwibeo/1wdgk1228942491.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/10/t1228942602osjpkwvznhwibeo/1wdgk1228942491.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/10/t1228942602osjpkwvznhwibeo/228ek1228942491.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/10/t1228942602osjpkwvznhwibeo/228ek1228942491.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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