Central tendency residuals: Bel 20

*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 14:08:44 -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/t1229289073fnasac6wbt86vtm.htm/, Retrieved Sun, 14 Dec 2008 22:11:13 +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/t1229289073fnasac6wbt86vtm.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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Dataseries X:

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3.03292821449275 11.8413874244167 58.7942231203385 -112.287518109905 2.31311402115942 -6.60735481318168 -136.410887763332 66.0268486886449 -71.9514696302174 112.798736426651 36.9441703382671 -22.3257593174066 -294.551408605613 107.587133339605 -2.48228467730405 52.525585278694 62.5346000587365 0.364349020119789 -6.94030071064526 57.1580377634591 -37.820795086815 -232.277034328264 -198.814613495449 -22.3274497956781 -73.1702151530176 -31.6763990470795 142.521988911548 -47.4464210896338 -1.75262190921467 -202.706782478373 -59.1596285173 234.812635844377 56.1752656277647 64.3922217233196 -59.6794511463945 83.8566184320798 -6.74205874461268 23.5173436086970 22.4003609728225 4.37023131072146 143.753183347962 31.5704580386823 -51.9193124480803 38.1988702853405 -102.309143222067 82.9518020495061 -45.2064497068209 77.0566125524124 114.651964696304 75.3228331641599 53.7366604885765 14.2159560590367 22.2717802213333 64.6954862290509 -15.5807821641924 -1.43588443930048 -84.5017273570957 52.6522460651281 46.4987565565029 94.9505015346685 -18.2499025718321 3.82867063178355 41.47756112561 110.149736152908 133.092928694232 84.5540561241187 40.2528491823596 -85.0637018498423 -112.050489105237 -225.829744546282 206.006886381846 129.342690026075 126.007744842466 97.7635350142564 -16.113689528579 61.3523859266516 88.1842051392878 10.5991343443029 -176.671625176693 245.280393939399 17.2612961086143 -50.570438757054 -101.958096976977 -360.686156574347 222.560020021611 97.7573748683571 -269.566007128316 73.7742064814001 -325.146570200226 55.8888973287399 -51.0091002933691 268.927309459710 -98.3835576601973 -258.464424396075 -437.940808276735 164.378147127013 -44.4208235424621 -625.134719492569 13.8063301316924

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 3 seconds R Server 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean -7.84446827643205 14.1963498475232 -0.552569383023527 Geometric Mean NaN Harmonic Mean 42.3794101054121 Quadratic Mean 140.755454188748 Winsorized Mean ( 1 / 33 ) -6.19247842092172 13.4167177208211 -0.461549430328386 Winsorized Mean ( 2 / 33 ) -4.84324824703554 12.8998347596927 -0.375450409812141 Winsorized Mean ( 3 / 33 ) -4.13758247275205 12.5379703618357 -0.330004167608056 Winsorized Mean ( 4 / 33 ) -3.57022780790971 12.1038699809892 -0.294965809573074 Winsorized Mean ( 5 / 33 ) -4.41080042293678 11.4553601381217 -0.385042492750472 Winsorized Mean ( 6 / 33 ) -4.98797503183436 11.1182042733763 -0.448631353516196 Winsorized Mean ( 7 / 33 ) -3.22339554274568 10.6881168391281 -0.301586854940167 Winsorized Mean ( 8 / 33 ) -3.46434668903529 10.4709644083581 -0.330852684999101 Winsorized Mean ( 9 / 33 ) -1.70319001633057 9.9814289662261 -0.170635890120904 Winsorized Mean ( 10 / 33 ) -1.64690478407653 9.85608042629024 -0.167095306942053 Winsorized Mean ( 11 / 33 ) -0.44832609823275 9.20014683601058 -0.0487303198768462 Winsorized Mean ( 12 / 33 ) 4.20712955555004 8.26754293581041 0.508873021672145 Winsorized Mean ( 13 / 33 ) 7.02699624177117 7.69407758685267 0.91329937376491 Winsorized Mean ( 14 / 33 ) 6.69812721832784 7.63956816282627 0.87676778000628 Winsorized Mean ( 15 / 33 ) 6.68566472708866 7.21230916248354 0.92697977533543 Winsorized Mean ( 16 / 33 ) 6.74140389463463 7.20343839265214 0.935859172684976 Winsorized Mean ( 17 / 33 ) 6.87322532607451 7.04759627548013 0.97525809615226 Winsorized Mean ( 18 / 33 ) 8.06478158334256 6.53105194306829 1.23483653990872 Winsorized Mean ( 19 / 33 ) 7.47594000833219 6.42910434790545 1.16282760455860 Winsorized Mean ( 20 / 33 ) 9.62423788955223 6.08550052411836 1.58150309106194 Winsorized Mean ( 21 / 33 ) 9.69082891929724 6.02583387290678 1.60821375492427 Winsorized Mean ( 22 / 33 ) 11.1079020274593 5.49617888405455 2.02102265260787 Winsorized Mean ( 23 / 33 ) 10.8258716692711 5.43123845666786 1.99326023993299 Winsorized Mean ( 24 / 33 ) 12.2056751568977 5.15882028481104 2.36598184915154 Winsorized Mean ( 25 / 33 ) 10.4791232280987 4.89701780880459 2.13989894201687 Winsorized Mean ( 26 / 33 ) 10.2446765209750 4.84195721351198 2.11581310392131 Winsorized Mean ( 27 / 33 ) 11.0139728377992 4.7240420452228 2.33147222915535 Winsorized Mean ( 28 / 33 ) 11.1221121520460 4.5839632343122 2.42630919654722 Winsorized Mean ( 29 / 33 ) 11.0059399190758 4.51560585765459 2.43731190586954 Winsorized Mean ( 30 / 33 ) 12.2307476916012 4.17989119344324 2.92609236115689 Winsorized Mean ( 31 / 33 ) 13.6424096225966 3.88949662112094 3.50750005759482 Winsorized Mean ( 32 / 33 ) 16.3466284882796 3.50257913249253 4.66702617412298 Winsorized Mean ( 33 / 33 ) 16.2517358813619 3.49144860715212 4.65472579148686 Trimmed Mean ( 1 / 33 ) -4.33396854983417 12.6768435421232 -0.341880732016062 Trimmed Mean ( 2 / 33 ) -2.39720563154293 11.8112337889455 -0.202959798644113 Trimmed Mean ( 3 / 33 ) -1.09527972329686 11.1357423576242 -0.0983571357994802 Trimmed Mean ( 4 / 33 ) 0.00797292210996413 10.5168218880853 0.000758111356720495 Trimmed Mean ( 5 / 33 ) 1.00303436107611 9.95748181015866 0.100731729186069 Trimmed Mean ( 6 / 33 ) 2.23514848433422 9.50894709850679 0.235057410792117 Trimmed Mean ( 7 / 33 ) 3.63728422570812 9.0776626637732 0.400685105894456 Trimmed Mean ( 8 / 33 ) 4.80631571809525 8.68445022438759 0.553439261428225 Trimmed Mean ( 9 / 33 ) 6.06988914140686 8.27317675457525 0.733683000070085 Trimmed Mean ( 10 / 33 ) 7.1522166190665 7.90081851241175 0.905250083624978 Trimmed Mean ( 11 / 33 ) 8.28353222804204 7.48663187862442 1.10644310583680 Trimmed Mean ( 12 / 33 ) 9.33135522719501 7.13319348321567 1.30815955702752 Trimmed Mean ( 13 / 33 ) 9.9104629229631 6.9026004213106 1.43575787646149 Trimmed Mean ( 14 / 33 ) 10.2197404976522 6.7349916847559 1.51740951971533 Trimmed Mean ( 15 / 33 ) 10.5806511753469 6.54514709369345 1.61656430694153 Trimmed Mean ( 16 / 33 ) 10.9643364075634 6.39152132588662 1.71545017978054 Trimmed Mean ( 17 / 33 ) 11.3663270986979 6.20852624241369 1.83076090120206 Trimmed Mean ( 18 / 33 ) 11.7816558339825 6.01475190511662 1.95879331680498 Trimmed Mean ( 19 / 33 ) 12.1167838401877 5.86936748978697 2.06441049419236 Trimmed Mean ( 20 / 33 ) 12.5266353471937 5.70799452881626 2.19457732202688 Trimmed Mean ( 21 / 33 ) 12.7786856527257 5.57072700097285 2.29389909979327 Trimmed Mean ( 22 / 33 ) 13.0433590870196 5.41073927393645 2.41064269162801 Trimmed Mean ( 23 / 33 ) 13.2076903467935 5.30500354250308 2.48966664036603 Trimmed Mean ( 24 / 33 ) 13.4087134065333 5.18160016757398 2.58775532130864 Trimmed Mean ( 25 / 33 ) 13.5099895857118 5.07397041656304 2.66260708608212 Trimmed Mean ( 26 / 33 ) 13.7653561979703 4.9804824911376 2.76385997189322 Trimmed Mean ( 27 / 33 ) 13.7653561979703 4.86649484865232 2.82859771274233 Trimmed Mean ( 28 / 33 ) 14.3232765860214 4.73976932603994 3.02193537295800 Trimmed Mean ( 29 / 33 ) 14.5993351913903 4.5999265495806 3.17381919776990 Trimmed Mean ( 30 / 33 ) 14.9138764221234 4.42574104499283 3.36980321950753 Trimmed Mean ( 31 / 33 ) 15.1531824980889 4.27293819486386 3.54631445788365 Trimmed Mean ( 32 / 33 ) 15.2910318203689 4.13649208237688 3.69661817691247 Trimmed Mean ( 33 / 33 ) 15.1920696327523 4.04456478144619 3.75616919339344 Median 11.8413874244167 Midrange -178.103705016430 Midmean - Weighted Average at Xnp 12.2014035450360 Midmean - Weighted Average at X(n+1)p 13.4087134065333 Midmean - Empirical Distribution Function 13.4087134065333 Midmean - Empirical Distribution Function - Averaging 13.4087134065333 Midmean - Empirical Distribution Function - Interpolation 13.5099895857118 Midmean - Closest Observation 12.2014035450360 Midmean - True Basic - Statistics Graphics Toolkit 13.4087134065333 Midmean - MS Excel (old versions) 13.4087134065333 Number of observations 99

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/14/t1229289073fnasac6wbt86vtm/12wwe1229288916.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/14/t1229289073fnasac6wbt86vtm/12wwe1229288916.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/14/t1229289073fnasac6wbt86vtm/229n51229288916.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/14/t1229289073fnasac6wbt86vtm/229n51229288916.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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