Voorspelling part 3

*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: Tue, 20 Oct 2009 07:30:05 -0600

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Oct/20/t1256045537trkmfnvk5v7dnei.htm/, Retrieved Tue, 20 Oct 2009 15:32:20 +0200

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/2009/Oct/20/t1256045537trkmfnvk5v7dnei.htm/}, year = {2009}, } @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 = {2009}, 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:

JSSHWWS3P3

Dataseries X:

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-0.015158266 -0.012632086 -0.017036831 0.026691427 0.033424189 0.027363463 0.018495535 0.023007715 0.028158094 0.045505923 0.070845156 0.093632358 0.10622399 0.085692634 0.074952835 0.127942072 0.156524445 0.126013756 0.105495384 0.104535743 0.078282247 0.043839817 0.08941521 0.071281408 0.071522155 0.043960101 0.046678703 0.092693659 0.084585679 0.082734299 0.06424205 0.037557065 0.008675224 -0.001929849 0.003403189 0.006208308 -0.006908817 0.007550396 0.010493005 0.034684797 0.028380955 0.011577493 0.013326917 -0.008846281 -0.032707147 -0.05018572 -0.044022282 -0.04723139 -0.040809446 -0.040791122 -0.039629471 -0.014180609 -0.027279208 -0.032682748 -0.046843645 -0.065226751 -0.081925576 -0.081660448 -0.071741896 -0.071919641 -0.063600328 -0.056074338 -0.049774243 -0.021242457 -0.035062419 -0.038027983 -0.040482844 -0.05702195 -0.072433603 -0.08351678 -0.079245278 -0.081160437 -0.07519985 -0.073845775 -0.069375723 -0.042705605 -0.039 etc...

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 3.41880341914973e-11 0.00512375232924746 6.6724603366062e-09 Geometric Mean NaN Harmonic Mean -0.0186828759039334 Quadratic Mean 0.0551845014478738 Winsorized Mean ( 1 / 39 ) -0.000230693717948718 0.00506299331886795 -0.0455646893881937 Winsorized Mean ( 2 / 39 ) -0.000259124282051282 0.00505521767027965 -0.0512587783459278 Winsorized Mean ( 3 / 39 ) -0.000753733384615384 0.00495146559901172 -0.152224299966019 Winsorized Mean ( 4 / 39 ) -0.00071316747008547 0.00493776470705473 -0.144431238099812 Winsorized Mean ( 5 / 39 ) -0.000581296230769231 0.00490699088467699 -0.118462871529768 Winsorized Mean ( 6 / 39 ) -0.00107100443589744 0.00479866071882947 -0.223188197426611 Winsorized Mean ( 7 / 39 ) -0.00104267699145299 0.00477816994257062 -0.218216807686844 Winsorized Mean ( 8 / 39 ) -0.00123170174358974 0.00473619552137019 -0.260061422302391 Winsorized Mean ( 9 / 39 ) -0.00150438105128205 0.00468784817137464 -0.32091078812412 Winsorized Mean ( 10 / 39 ) -0.00148514669230769 0.00465811359743641 -0.318830071710798 Winsorized Mean ( 11 / 39 ) -0.00156197783760684 0.00461819969765965 -0.338222238072207 Winsorized Mean ( 12 / 39 ) -0.00198377445299145 0.00454307164069615 -0.436659293509946 Winsorized Mean ( 13 / 39 ) -0.00193919900854701 0.00443534380664700 -0.437215037454557 Winsorized Mean ( 14 / 39 ) -0.00234027316239316 0.00437361475745198 -0.535089003530933 Winsorized Mean ( 15 / 39 ) -0.00217691047008547 0.0043452248625985 -0.500989140705516 Winsorized Mean ( 16 / 39 ) -0.00222132824786325 0.00433468256318926 -0.512454652787515 Winsorized Mean ( 17 / 39 ) -0.00201226384615385 0.00411389302402838 -0.489138593152675 Winsorized Mean ( 18 / 39 ) -0.002091644 0.00406533270247502 -0.514507459309931 Winsorized Mean ( 19 / 39 ) -0.00326265135042735 0.00389075890223974 -0.838564257618016 Winsorized Mean ( 20 / 39 ) -0.00365097049572650 0.00383269811093078 -0.952584938874783 Winsorized Mean ( 21 / 39 ) -0.00426063603418803 0.00359288454303793 -1.18585386843116 Winsorized Mean ( 22 / 39 ) -0.00403413268376068 0.00354799548997100 -1.13701742157335 Winsorized Mean ( 23 / 39 ) -0.00418379053846154 0.00351066258461202 -1.19173815131080 Winsorized Mean ( 24 / 39 ) -0.00425145084615385 0.0034443911543743 -1.2343112775547 Winsorized Mean ( 25 / 39 ) -0.00410376986324786 0.00342214390241344 -1.19918097551471 Winsorized Mean ( 26 / 39 ) -0.00429918230769231 0.00337916767813946 -1.27226072133224 Winsorized Mean ( 27 / 39 ) -0.00477321392307692 0.00331590318536892 -1.43949134104344 Winsorized Mean ( 28 / 39 ) -0.0053585981965812 0.00322693629023386 -1.66058382150236 Winsorized Mean ( 29 / 39 ) -0.00544259533333333 0.00312860303371104 -1.73962477012544 Winsorized Mean ( 30 / 39 ) -0.00536875430769231 0.00306726579021594 -1.75033879516335 Winsorized Mean ( 31 / 39 ) -0.00535389841880342 0.00299208163395679 -1.78935573082052 Winsorized Mean ( 32 / 39 ) -0.00621463688034188 0.00278539353157676 -2.23115219084461 Winsorized Mean ( 33 / 39 ) -0.0062723268034188 0.00277811697138947 -2.25776195459535 Winsorized Mean ( 34 / 39 ) -0.00647013444444444 0.00274998644054448 -2.35278776253289 Winsorized Mean ( 35 / 39 ) -0.00651925918803419 0.00273239416343931 -2.38591462215257 Winsorized Mean ( 36 / 39 ) -0.00635313857264957 0.00269414577637771 -2.35812725070557 Winsorized Mean ( 37 / 39 ) -0.00664309966666667 0.00266246094887423 -2.4950975034866 Winsorized Mean ( 38 / 39 ) -0.00667832631623932 0.00255880366537201 -2.60994089019659 Winsorized Mean ( 39 / 39 ) -0.00700208564957265 0.00251657247173292 -2.78238982911189 Trimmed Mean ( 1 / 39 ) -0.000634849226086957 0.00497731093960643 -0.127548636962825 Trimmed Mean ( 2 / 39 ) -0.00105331112389381 0.00488183876962827 -0.215761145256751 Trimmed Mean ( 3 / 39 ) -0.00147186905405405 0.0047798308723753 -0.307933291648585 Trimmed Mean ( 4 / 39 ) -0.00172881667889908 0.00470866639924977 -0.367156330967625 Trimmed Mean ( 5 / 39 ) -0.00200645910280374 0.00463334994080662 -0.433047175032593 Trimmed Mean ( 6 / 39 ) -0.00232406682857143 0.00455702749883157 -0.509996226524269 Trimmed Mean ( 7 / 39 ) -0.00256129708737864 0.0044967719987937 -0.569585713499758 Trimmed Mean ( 8 / 39 ) -0.00281261045544554 0.00443299246597569 -0.63447219390356 Trimmed Mean ( 9 / 39 ) -0.00304615378787879 0.00436898671780501 -0.697222029873596 Trimmed Mean ( 10 / 39 ) -0.00325278312371134 0.00430518539082308 -0.755550070072467 Trimmed Mean ( 11 / 39 ) -0.00347048150526316 0.00423767849799057 -0.818958188288421 Trimmed Mean ( 12 / 39 ) -0.00368875611827957 0.00416727468062462 -0.885172301079676 Trimmed Mean ( 13 / 39 ) -0.00387143272527473 0.00409878704297118 -0.94453131735977 Trimmed Mean ( 14 / 39 ) -0.00406682714606742 0.00403637749569633 -1.00754380639659 Trimmed Mean ( 15 / 39 ) -0.00406682714606742 0.00397373441855250 -1.02342701290763 Trimmed Mean ( 16 / 39 ) -0.00442132532941176 0.00390542687703931 -1.13209783939510 Trimmed Mean ( 17 / 39 ) -0.00461515037349398 0.00382798532791714 -1.20563429014111 Trimmed Mean ( 18 / 39 ) -0.00483631066666667 0.00376869990001843 -1.28328357125040 Trimmed Mean ( 19 / 39 ) -0.00506213767088608 0.00370607230257976 -1.36590364612217 Trimmed Mean ( 20 / 39 ) -0.00520604737662338 0.00365681122836366 -1.42365767645954 Trimmed Mean ( 21 / 39 ) -0.00532734337333333 0.00360639183311529 -1.47719483069355 Trimmed Mean ( 22 / 39 ) -0.00540875547945205 0.00357756389903343 -1.51185433219330 Trimmed Mean ( 23 / 39 ) -0.00551172018309859 0.00354767811098955 -1.55361338054461 Trimmed Mean ( 24 / 39 ) -0.00560962047826087 0.00351558117268296 -1.59564527249411 Trimmed Mean ( 25 / 39 ) -0.00570844252238806 0.00348439337118075 -1.63828876773854 Trimmed Mean ( 26 / 39 ) -0.00582397895384615 0.00344825643724478 -1.68896341088241 Trimmed Mean ( 27 / 39 ) -0.005932893 0.00340908664391517 -1.74031745734287 Trimmed Mean ( 28 / 39 ) -0.00601527457377049 0.00336906366202907 -1.78544402160323 Trimmed Mean ( 29 / 39 ) -0.00606178252542373 0.00333137358729929 -1.81960454646516 Trimmed Mean ( 30 / 39 ) -0.00606178252542373 0.00329732666833775 -1.83839307874206 Trimmed Mean ( 31 / 39 ) -0.00615785852727273 0.00326200975705561 -1.88774987994855 Trimmed Mean ( 32 / 39 ) -0.00621510949056604 0.00322703181123659 -1.92595234696011 Trimmed Mean ( 33 / 39 ) -0.00621514337254902 0.00321190163961659 -1.93503539955568 Trimmed Mean ( 34 / 39 ) -0.00621100579591837 0.00318969278178486 -1.94721128987315 Trimmed Mean ( 35 / 39 ) -0.00619203329787234 0.00316186795662307 -1.95834657955974 Trimmed Mean ( 36 / 39 ) -0.00616772508888889 0.00312504343436961 -1.97364459676160 Trimmed Mean ( 37 / 39 ) -0.00615371127906977 0.00308041488087542 -1.99768911560411 Trimmed Mean ( 38 / 39 ) -0.00611596675609756 0.0030242103331367 -2.02233511640511 Trimmed Mean ( 39 / 39 ) -0.00607156994871795 0.00296793174222024 -2.04572425381183 Median -0.006908817 Midrange 0.0365038325 Midmean - Weighted Average at Xnp -0.00678044486206896 Midmean - Weighted Average at X(n+1)p -0.00606178252542372 Midmean - Empirical Distribution Function -0.00606178252542372 Midmean - Empirical Distribution Function - Averaging -0.00606178252542372 Midmean - Empirical Distribution Function - Interpolation -0.00606178252542372 Midmean - Closest Observation -0.00674148023333332 Midmean - True Basic - Statistics Graphics Toolkit -0.00606178252542372 Midmean - MS Excel (old versions) -0.00606178252542372 Number of observations 117

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Oct/20/t1256045537trkmfnvk5v7dnei/1u68k1256045403.png (open in new window) http://www.freestatistics.org/blog/date/2009/Oct/20/t1256045537trkmfnvk5v7dnei/1u68k1256045403.ps (open in new window) http://www.freestatistics.org/blog/date/2009/Oct/20/t1256045537trkmfnvk5v7dnei/2i2z01256045403.png (open in new window) http://www.freestatistics.org/blog/date/2009/Oct/20/t1256045537trkmfnvk5v7dnei/2i2z01256045403.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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