PAPER-ARIMA.RESIDUALS

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

Title produced by software: Central Tendency

Date of computation: Wed, 02 Jan 2008 14:13:05 -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/Jan/02/t1199308452rdpu1f4z950sf5j.htm/, Retrieved Wed, 02 Jan 2008 22:14:12 +0100

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Dataseries X:

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-26.9187469810876 32.874489387891 55.4109661945276 -411.740218895421 57.6733737633629 -449.467581034991 -373.137339219786 -371.885252056547 647.419900104101 22.1523873805244 120.184757841137 67.8888120330147 -152.178661396321 231.692050126901 145.757895879761 225.957394333699 337.679772954793 659.938431816578 220.144078002751 568.176791409846 348.725688751759 -773.427863750167 498.38970904353 -602.642890302524 -236.529593612675 -3.05556298875158 392.249606246461 -104.550624189284 682.677984138286 -319.622690005149 315.541866099491 -660.840435525499 -420.191537655717 -277.196634339462 214.812779686457 -48.212892846644 -710.905914493365 -581.694767515458 -463.052581193947 23.9970209408294 -281.457845858963 -536.338283342713 35.4711023289096 241.984285406962 380.351841879643 500.008616361698 182.200659128449 -675.434091344352 198.846676202320 -126.639122463669 186.007671918163 601.909319356326 20.3167698321624 -68.1288115494744 259.690820578064 -61.7095797836514 -647.712668790697 -295.901619150497 -605.509356504182 -98.046012972324 270.083300740681 -442.289624599786 -38.8754805600827 660.951580547094 -57.6441355331235 -231.023829802187 -252.085124727441 115.231007902820 748.358137075023 405.44716695319 -849.686777864503 695.692017672714 175.799998798506 244.333601485961 7.89489659545201 74.8741067960001 -21.1310352998892 462.378548091352 -214.580694018194 -464.829610996476 100.794657909799 517.088499003938 -359.030784626636 -227.25098999516 -634.829213278288 163.911850756588 844.727539602654 -309.728276460699 715.917713811229 831.323237867774 575.22343178314 -675.977088920678 964.105083611734 -985.20223413236 -90.6798507383488 -121.024474917569 -166.838259312123 -26.9771629104613 6.1385957833859 171.057951354712 18.1599006949306 -1161.16622559775 17.8684254754743 -34.0938501480774 413.474910175273 -307.711577223802 602.475786753365 540.065609154372

Text written by user:

Output produced by software:

Summary of compuational 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 7.06227401943153 41.7929872098684 0.168982274082671 Geometric Mean NaN Harmonic Mean 1159.72637483162 Quadratic Mean 432.36770250126 Winsorized Mean ( 1 / 36 ) 7.58622260698996 41.1729677818004 0.184252508762394 Winsorized Mean ( 2 / 36 ) 9.84754028352657 40.5946013398464 0.242582509952143 Winsorized Mean ( 3 / 36 ) 9.66125732023727 39.7718365195224 0.242917053013002 Winsorized Mean ( 4 / 36 ) 10.7753879125709 39.1538105260638 0.275206621470418 Winsorized Mean ( 5 / 36 ) 11.4560883493381 38.7242360592609 0.295837685004464 Winsorized Mean ( 6 / 36 ) 10.7632530183325 38.6007207722639 0.278835545114128 Winsorized Mean ( 7 / 36 ) 10.3009452923475 38.2179387820214 0.269531681211267 Winsorized Mean ( 8 / 36 ) 11.1983244037761 38.0474942475072 0.294324885915708 Winsorized Mean ( 9 / 36 ) 11.2287347204371 37.7092873525515 0.29777106672575 Winsorized Mean ( 10 / 36 ) 9.78204429667507 36.6359534195245 0.267006680149940 Winsorized Mean ( 11 / 36 ) 10.0163034341826 36.5814681735145 0.273808131119092 Winsorized Mean ( 12 / 36 ) 9.37877401350256 35.7762034488022 0.262151181774335 Winsorized Mean ( 13 / 36 ) 13.9901441004735 34.8255519946948 0.40172067057558 Winsorized Mean ( 14 / 36 ) 19.6157446677947 32.9632529302076 0.595079154030297 Winsorized Mean ( 15 / 36 ) 16.6712890639189 32.4638998208283 0.513533160092581 Winsorized Mean ( 16 / 36 ) 16.1535286960250 31.8252621145989 0.507569384279009 Winsorized Mean ( 17 / 36 ) 17.0285642051883 31.635134072954 0.538280133914355 Winsorized Mean ( 18 / 36 ) 14.7097185371701 30.2967120718113 0.485521943843415 Winsorized Mean ( 19 / 36 ) 7.5931068338379 28.9376993885715 0.262394972450252 Winsorized Mean ( 20 / 36 ) 13.2551691400512 27.7933745622429 0.476918306928380 Winsorized Mean ( 21 / 36 ) 10.9324381732615 27.4257233685189 0.398619865968986 Winsorized Mean ( 22 / 36 ) 11.1273221305582 26.7720607606461 0.415631886915294 Winsorized Mean ( 23 / 36 ) 12.7845874486403 24.8445334826128 0.51458351824507 Winsorized Mean ( 24 / 36 ) 12.5286980591923 24.2617431080991 0.51639727629504 Winsorized Mean ( 25 / 36 ) 7.87101111048749 23.5699348406744 0.333942845565469 Winsorized Mean ( 26 / 36 ) -0.229579532319273 21.9131243808587 -0.0104768050565994 Winsorized Mean ( 27 / 36 ) 0.783243749909978 21.1620378069566 0.0370117356870283 Winsorized Mean ( 28 / 36 ) -2.09349895409794 20.5736165959597 -0.101756487214264 Winsorized Mean ( 29 / 36 ) 4.01857153162091 19.6708514873425 0.204290675175232 Winsorized Mean ( 30 / 36 ) 5.48059815237231 18.8261685923994 0.291115960503242 Winsorized Mean ( 31 / 36 ) 5.41489767585255 18.4522447363895 0.293454685498175 Winsorized Mean ( 32 / 36 ) 4.81031203913522 18.1266117236746 0.265372928623644 Winsorized Mean ( 33 / 36 ) 7.05278354656278 17.4847679022984 0.403367295806978 Winsorized Mean ( 34 / 36 ) 17.0564433756901 15.1807211852401 1.12355949151308 Winsorized Mean ( 35 / 36 ) 17.6464505711307 14.1821438924047 1.24427242488925 Winsorized Mean ( 36 / 36 ) 24.89062595211 13.1035498899223 1.89953303961187 Trimmed Mean ( 1 / 36 ) 9.05459184985492 40.1067998808519 0.225762012345887 Trimmed Mean ( 2 / 36 ) 10.5794368328301 38.9078926096188 0.271909788046825 Trimmed Mean ( 3 / 36 ) 10.9669114765790 37.9057549798321 0.289320486623046 Trimmed Mean ( 4 / 36 ) 11.436946972862 37.1229830255481 0.308082649634893 Trimmed Mean ( 5 / 36 ) 11.6192132445749 36.4436156585289 0.318827126085543 Trimmed Mean ( 6 / 36 ) 11.6559163460031 35.7938283027262 0.325640393852908 Trimmed Mean ( 7 / 36 ) 11.8268518768337 35.0868469166465 0.337073659110206 Trimmed Mean ( 8 / 36 ) 12.0827492543562 34.3673815695831 0.351576078901805 Trimmed Mean ( 9 / 36 ) 12.2154129819432 33.5819608872944 0.363749246892992 Trimmed Mean ( 10 / 36 ) 12.3499600176032 32.7491438531606 0.37710787411657 Trimmed Mean ( 11 / 36 ) 12.6724424569755 31.9907254117225 0.396128637093422 Trimmed Mean ( 12 / 36 ) 12.9829002648344 31.1274111944974 0.417088982559831 Trimmed Mean ( 13 / 36 ) 13.3784750972977 30.2690725611872 0.441984968989515 Trimmed Mean ( 14 / 36 ) 13.3149556238910 29.4343338795628 0.45236137085256 Trimmed Mean ( 15 / 36 ) 12.6918006635049 28.7646729627645 0.441228748887021 Trimmed Mean ( 16 / 36 ) 12.3147964992551 28.0620970386710 0.43884092062987 Trimmed Mean ( 17 / 36 ) 11.9646418731984 27.3389263290430 0.437641249301294 Trimmed Mean ( 18 / 36 ) 11.5178251968464 26.5172434671709 0.434352281416647 Trimmed Mean ( 19 / 36 ) 11.2442343391044 25.7593649815817 0.436510540812794 Trimmed Mean ( 20 / 36 ) 11.5494369479037 25.0732469233120 0.460627894872506 Trimmed Mean ( 21 / 36 ) 11.4098770412735 24.4332947094444 0.466980698958422 Trimmed Mean ( 22 / 36 ) 11.4482426645959 23.7229133347764 0.482581650197803 Trimmed Mean ( 23 / 36 ) 11.4736527948569 22.9717752973272 0.499467396243941 Trimmed Mean ( 24 / 36 ) 11.3710579089086 22.3758745016149 0.508183843634267 Trimmed Mean ( 25 / 36 ) 11.2812410006970 21.7422043204504 0.518863719355539 Trimmed Mean ( 26 / 36 ) 11.5443158779417 21.0787707854939 0.547675004174643 Trimmed Mean ( 27 / 36 ) 12.4500001402695 20.5368139032048 0.606228414930838 Trimmed Mean ( 28 / 36 ) 13.3474429395279 19.9880004498287 0.667772795634608 Trimmed Mean ( 29 / 36 ) 14.5386013141790 19.3958343979444 0.74957338858904 Trimmed Mean ( 30 / 36 ) 15.3548105214465 18.8173651834632 0.815991525473519 Trimmed Mean ( 31 / 36 ) 16.1275749677218 18.2383482562579 0.884267299928775 Trimmed Mean ( 32 / 36 ) 16.9757928178112 17.5601545663466 0.966722289013599 Trimmed Mean ( 33 / 36 ) 17.9533760946691 16.7382505131093 1.07259573398116 Trimmed Mean ( 34 / 36 ) 18.8452427576960 15.8031466860293 1.19249938838801 Trimmed Mean ( 35 / 36 ) 18.9947708794116 15.1501213762858 1.25377021131618 Trimmed Mean ( 36 / 36 ) 19.1103411915500 14.5165387891321 1.31645301053837 Median 18.0141630852024 Midrange -98.530570993008 Midmean - Weighted Average at Xnp 6.8436070622555 Midmean - Weighted Average at X(n+1)p 12.4500001402694 Midmean - Empirical Distribution Function 6.8436070622555 Midmean - Empirical Distribution Function - Averaging 12.4500001402694 Midmean - Empirical Distribution Function - Interpolation 12.4500001402694 Midmean - Closest Observation 6.8436070622555 Midmean - True Basic - Statistics Graphics Toolkit 12.4500001402694 Midmean - MS Excel (old versions) 11.5443158779417 Number of observations 108

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Jan/02/t1199308452rdpu1f4z950sf5j/151y21199308379.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Jan/02/t1199308452rdpu1f4z950sf5j/151y21199308379.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Jan/02/t1199308452rdpu1f4z950sf5j/2smj71199308379.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Jan/02/t1199308452rdpu1f4z950sf5j/2smj71199308379.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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