Central tendency residuals olieprijs paper

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R Software Module: rwasp_centraltendency.wasp (opens new window with default values)

Title produced by software: Central Tendency

Date of computation: Tue, 16 Dec 2008 09:14:21 -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/16/t1229444114c6ecijxvmqk3xnn.htm/, Retrieved Tue, 16 Dec 2008 17:15:14 +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/16/t1229444114c6ecijxvmqk3xnn.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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0.0326799749060955 -0.919935822834049 1.51438670308095 -6.1631139939367 2.12340885441733 3.24952327755486 -3.84838574106211 0.936801191460468 3.65569332670514 -2.93206643679393 -2.11031603933376 2.36339063771391 0.0247479307498209 -4.9922982055694 0.0483877904918534 2.11795847710773 0.0762799846864839 0.231553770062301 3.61544787500945 -0.499230224455294 -1.77179269273372 -0.369957806209545 1.41880336898059 0.109832314133829 1.73829053728576 -2.11596435891139 -2.68553870953056 5.10297645786464 1.16984141439419 -0.0919864702520208 -3.36899837437685 -3.85402642643007 3.95873565664667 1.6288585804114 -0.614486587517071 0.937721029422274 -3.40784618818261 3.47687736525095 -0.945621124167502 0.189705403122648 1.3267866922961 -1.29142498174907 2.43621688952784 -0.63166224123475 3.32717311694248 -3.44447122885173 2.40173030359632 3.81312885193559 -2.07403053846616 5.72389913906567 -7.77720472363209 -2.78341365354723 8.02895456764453 -1.20519052475994 6.0593920145338 -3.78389142239353 -2.56208463510965 5.58089741321821 0.105442616758097 4.43762073648554 -3.40498044662028 -5.24892382454493 0.425397103266526 3.07470460259579 5.36479734700345 -5.55073511161154 1.75707966091856 5.52218304857011 0.12673229744928 -4.50179137551679 5.85843401080328 -1.94132056543566 -11.2668131103917 2.34236607921895 2.54602816941789 2.66671893240986 -9.00670782119359 6.80640084593632 3.40377537038955 1.80578461517464 -2.23966881256965 1.63185235335440 4.54372230450109 -7.43378445448336 7.01096043209584 3.62995548847748 6.44119408390861 -7.42702879962776 1.35250595771754 2.91968412171857 6.2308070370609 2.79694449985593 9.22922362226123 1.35589444625559 -3.33997102550251 -20.4900768370114 -4.14892777760734 -14.5321780805876 -7.60640602424891

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 2 seconds R Server 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 Central Tendency - Ungrouped Data Measure Value S.E. Value/S.E. Arithmetic Mean -0.026040025506756 0.47506329221714 -0.0548138025677087 Geometric Mean NaN Harmonic Mean 0.756082442512286 Quadratic Mean 4.7029587475251 Winsorized Mean ( 1 / 33 ) 0.0220168401680632 0.449494411400029 0.0489813435043338 Winsorized Mean ( 2 / 33 ) 0.0674182711710371 0.426006448820468 0.158256456815867 Winsorized Mean ( 3 / 33 ) 0.129707534899479 0.407816025217334 0.318054041231840 Winsorized Mean ( 4 / 33 ) 0.164628598961451 0.394596575481621 0.417207368717062 Winsorized Mean ( 5 / 33 ) 0.162629187473343 0.391133065834949 0.415789923376024 Winsorized Mean ( 6 / 33 ) 0.162702311548401 0.387396913505802 0.419988662470239 Winsorized Mean ( 7 / 33 ) 0.148970832335022 0.385122867405009 0.386813780596309 Winsorized Mean ( 8 / 33 ) 0.240233857300958 0.364017587918127 0.659951236628132 Winsorized Mean ( 9 / 33 ) 0.282904507889840 0.352316772484676 0.802983366061984 Winsorized Mean ( 10 / 33 ) 0.307459752578578 0.346334630212712 0.88775342041234 Winsorized Mean ( 11 / 33 ) 0.318486410068452 0.339049820202640 0.93934988633264 Winsorized Mean ( 12 / 33 ) 0.346205918058004 0.324987677190777 1.06528937050980 Winsorized Mean ( 13 / 33 ) 0.319104127947870 0.307379162650849 1.03814495815495 Winsorized Mean ( 14 / 33 ) 0.34580308718286 0.299199123802594 1.15576236583839 Winsorized Mean ( 15 / 33 ) 0.274099391050904 0.289292099529278 0.94748315455868 Winsorized Mean ( 16 / 33 ) 0.260990302397571 0.284751631153499 0.916554196161499 Winsorized Mean ( 17 / 33 ) 0.292240194935883 0.273034327034064 1.07034231962863 Winsorized Mean ( 18 / 33 ) 0.294219686288876 0.271518664860579 1.08360759080763 Winsorized Mean ( 19 / 33 ) 0.291985387640308 0.271093462892541 1.07706539480831 Winsorized Mean ( 20 / 33 ) 0.271260450768576 0.266612782840715 1.01743227717119 Winsorized Mean ( 21 / 33 ) 0.261911283437988 0.263861698077798 0.992608193405791 Winsorized Mean ( 22 / 33 ) 0.335534024607212 0.249406585514765 1.34532945036188 Winsorized Mean ( 23 / 33 ) 0.352029658029019 0.242617229683940 1.45096726431017 Winsorized Mean ( 24 / 33 ) 0.333376632346012 0.234381183637321 1.42236943756490 Winsorized Mean ( 25 / 33 ) 0.325405317584318 0.225664105370895 1.44198970877310 Winsorized Mean ( 26 / 33 ) 0.377845531903625 0.210994736319135 1.79078179150461 Winsorized Mean ( 27 / 33 ) 0.376067046325131 0.202615167709618 1.85606561727945 Winsorized Mean ( 28 / 33 ) 0.343529789601884 0.198512610337326 1.73051872633247 Winsorized Mean ( 29 / 33 ) 0.321991935140762 0.193557081244252 1.66355027194503 Winsorized Mean ( 30 / 33 ) 0.351756597898028 0.187339454839638 1.87764290335494 Winsorized Mean ( 31 / 33 ) 0.39283573336677 0.179412650886103 2.18956540370252 Winsorized Mean ( 32 / 33 ) 0.541310287706872 0.159981147186575 3.38358798662432 Winsorized Mean ( 33 / 33 ) 0.497069365102709 0.148339277013052 3.35089515812439 Trimmed Mean ( 1 / 33 ) 0.089514337005993 0.425238110028162 0.210504032670225 Trimmed Mean ( 2 / 33 ) 0.159853833710783 0.396875618328833 0.402780685757157 Trimmed Mean ( 3 / 33 ) 0.209053407320648 0.378975744796633 0.551627406742959 Trimmed Mean ( 4 / 33 ) 0.237827185231621 0.366534192730713 0.64885402221219 Trimmed Mean ( 5 / 33 ) 0.258182971862933 0.356886349484506 0.723431905523585 Trimmed Mean ( 6 / 33 ) 0.279929695206770 0.346822747429719 0.80712611061792 Trimmed Mean ( 7 / 33 ) 0.302685599093395 0.33619897098063 0.900316851686124 Trimmed Mean ( 8 / 33 ) 0.328877960382687 0.324429161411466 1.01371269756352 Trimmed Mean ( 9 / 33 ) 0.342420809464618 0.315517790625999 1.08526625007497 Trimmed Mean ( 10 / 33 ) 0.350707889430727 0.307569023812409 1.14025751060233 Trimmed Mean ( 11 / 33 ) 0.35626836416886 0.299468315923434 1.18966964191280 Trimmed Mean ( 12 / 33 ) 0.360802198660909 0.291353083389554 1.23836753146181 Trimmed Mean ( 13 / 33 ) 0.362451778318087 0.284354694467916 1.27464671893779 Trimmed Mean ( 14 / 33 ) 0.367101201272205 0.279101173546365 1.31529794951300 Trimmed Mean ( 15 / 33 ) 0.369283927250306 0.274196891688131 1.34678378364087 Trimmed Mean ( 16 / 33 ) 0.378660314398307 0.269882897276273 1.40305413281035 Trimmed Mean ( 17 / 33 ) 0.389861594386838 0.265370598457371 1.46912128417069 Trimmed Mean ( 18 / 33 ) 0.398885421226843 0.261734716594818 1.52400654531566 Trimmed Mean ( 19 / 33 ) 0.408322495688463 0.257480605551976 1.58583787238312 Trimmed Mean ( 20 / 33 ) 0.418596691671306 0.252290013873979 1.65918850787491 Trimmed Mean ( 21 / 33 ) 0.431391681012859 0.246595154043895 1.74939237020071 Trimmed Mean ( 22 / 33 ) 0.445918572233562 0.239972657316726 1.85820575235378 Trimmed Mean ( 23 / 33 ) 0.455290845145233 0.234316438228093 1.94305977245196 Trimmed Mean ( 24 / 33 ) 0.464005983699799 0.228391769685548 2.03162304989644 Trimmed Mean ( 25 / 33 ) 0.475002842359684 0.222342427298393 2.13635718621624 Trimmed Mean ( 26 / 33 ) 0.487607229553523 0.216209463788780 2.25525386821124 Trimmed Mean ( 27 / 33 ) 0.487607229553523 0.211166849428442 2.30910879654317 Trimmed Mean ( 28 / 33 ) 0.507197896005368 0.206150330414467 2.46033025989162 Trimmed Mean ( 29 / 33 ) 0.521312131662115 0.200205592048244 2.60388396911757 Trimmed Mean ( 30 / 33 ) 0.538759257617564 0.193205089528241 2.78853553461289 Trimmed Mean ( 31 / 33 ) 0.555437873214172 0.18520472529816 2.99904806597119 Trimmed Mean ( 32 / 33 ) 0.570274381826976 0.176321548009434 3.23428638340030 Trimmed Mean ( 33 / 33 ) 0.572989765650736 0.169641378210702 3.37765332782817 Median 0.231553770062301 Midrange -5.63042660737509 Midmean - Weighted Average at Xnp 0.411792011321879 Midmean - Weighted Average at X(n+1)p 0.464005983699799 Midmean - Empirical Distribution Function 0.464005983699799 Midmean - Empirical Distribution Function - Averaging 0.464005983699799 Midmean - Empirical Distribution Function - Interpolation 0.475002842359684 Midmean - Closest Observation 0.411792011321879 Midmean - True Basic - Statistics Graphics Toolkit 0.464005983699799 Midmean - MS Excel (old versions) 0.464005983699799 Number of observations 99

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/16/t1229444114c6ecijxvmqk3xnn/11w7s1229444055.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/16/t1229444114c6ecijxvmqk3xnn/11w7s1229444055.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/16/t1229444114c6ecijxvmqk3xnn/24nol1229444055.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/16/t1229444114c6ecijxvmqk3xnn/24nol1229444055.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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