Home » date » 2010 » Mar » 14 »

Wisselkoers Robustness Lordina Febiri

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Sun, 14 Mar 2010 14:38:36 -0600

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Mar/14/t1268599299oxy8ukx4jqvne3i.htm/, Retrieved Sun, 14 Mar 2010 21:41:41 +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/2010/Mar/14/t1268599299oxy8ukx4jqvne3i.htm/},
    year = {2010},
}
@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 = {2010},
    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:

KDGP1W52

Dataseries X:

» Textbox « » Textfile « » CSV «

0,8833 0,87 0,8758 0,8858 0,917 0,9554 0,9922 0,9778 0,9808 0,9811 1,0014 1,0183 1,0622 1,0773 1,0807 1,0848 1,1582 1,1663 1,1372 1,1139 1,1222 1,1692 1,1702 1,2286 1,2613 1,2646 1,2262 1,1985 1,2007 1,2138 1,2266 1,2176 1,2218 1,249 1,2991 1,3408 1,3119 1,3014 1,3201 1,2938 1,2694 1,2165 1,2037 1,2292 1,2256 1,2015 1,1786 1,1856 1,2103 1,1938 1,202 1,2271 1,277 1,265 1,2684 1,2811 1,2727 1,2611 1,2881 1,3213 1,2999 1,3074 1,3242 1,3516 1,3511 1,3419 1,3716 1,3622 1,3896 1,4227 1,4684 1,457 1,4718 1,4748 1,5527 1,575 1,5557 1,5553 1,577 1,4975 1,4369 1,3322 1,2732 1,3449 1,3239 1,2785 1,305 1,319 1,365 1,4016 1,4088 1,4268 1,4562 1,4816 1,4914 1,4614 1,4272

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	1.25851443298969	0.0168859322479287	74.5303495543793
Geometric Mean	1.24701367517144
Harmonic Mean	1.23481514243779
Quadratic Mean	1.26934294420381
Winsorized Mean ( 1 / 32 )	1.25855360824742	0.01686765998328	74.6134087060658
Winsorized Mean ( 2 / 32 )	1.25831030927835	0.0167556814801849	75.0975309936759
Winsorized Mean ( 3 / 32 )	1.25837525773196	0.0167354163464729	75.1923484710416
Winsorized Mean ( 4 / 32 )	1.25955463917526	0.0164265313494623	76.6780650387574
Winsorized Mean ( 5 / 32 )	1.25868865979381	0.0155160503222860	81.1217180693164
Winsorized Mean ( 6 / 32 )	1.25969690721649	0.0151806628511299	82.9803625552977
Winsorized Mean ( 7 / 32 )	1.25920618556701	0.0150280968824162	83.7901296098483
Winsorized Mean ( 8 / 32 )	1.25867010309278	0.0149378238268073	84.2606070125145
Winsorized Mean ( 9 / 32 )	1.25942164948454	0.0146986921586380	85.6825652168248
Winsorized Mean ( 10 / 32 )	1.26001958762887	0.0144678992518304	87.0907078973095
Winsorized Mean ( 11 / 32 )	1.26114226804124	0.0139975066688571	90.0976365203055
Winsorized Mean ( 12 / 32 )	1.26602886597938	0.0129785489123475	97.5477978724505
Winsorized Mean ( 13 / 32 )	1.26794536082474	0.0126373870894969	100.332873547773
Winsorized Mean ( 14 / 32 )	1.26565051546392	0.0121388688638272	104.264287691207
Winsorized Mean ( 15 / 32 )	1.26478453608247	0.011820679007196	106.997621313676
Winsorized Mean ( 16 / 32 )	1.26951855670103	0.0110782929457432	114.595142312863
Winsorized Mean ( 17 / 32 )	1.27025463917526	0.0107614531832244	118.037463672230
Winsorized Mean ( 18 / 32 )	1.27045876288660	0.00999195775758778	127.148131898559
Winsorized Mean ( 19 / 32 )	1.27316185567010	0.00923494972832818	137.863431109396
Winsorized Mean ( 20 / 32 )	1.27235773195876	0.00866644505173446	146.814261714395
Winsorized Mean ( 21 / 32 )	1.26908865979381	0.00805232763891286	157.605194013833
Winsorized Mean ( 22 / 32 )	1.26781855670103	0.00782685088529905	161.983226112349
Winsorized Mean ( 23 / 32 )	1.26914639175258	0.00748598878264012	169.536240115094
Winsorized Mean ( 24 / 32 )	1.26825567010309	0.00693513732082214	182.873908825895
Winsorized Mean ( 25 / 32 )	1.27024020618557	0.00666132695194625	190.688764468232
Winsorized Mean ( 26 / 32 )	1.26983814432990	0.00630355805598402	201.447838356058
Winsorized Mean ( 27 / 32 )	1.26961546391753	0.00612849895504793	207.165812253548
Winsorized Mean ( 28 / 32 )	1.26952886597938	0.00606252926424419	209.405812433246
Winsorized Mean ( 29 / 32 )	1.26710721649485	0.00573539573849186	220.927600163827
Winsorized Mean ( 30 / 32 )	1.26515876288660	0.00538537433898512	234.924943606616
Winsorized Mean ( 31 / 32 )	1.26717216494845	0.00512705677910938	247.153916865452
Winsorized Mean ( 32 / 32 )	1.26746907216495	0.0048958520386039	258.886310732213
Trimmed Mean ( 1 / 32 )	1.25925157894737	0.016403186595555	76.7687163473837
Trimmed Mean ( 2 / 32 )	1.25997956989247	0.0158739659401296	79.3739620359915
Trimmed Mean ( 3 / 32 )	1.26086923076923	0.0153372932211384	82.2093711445416
Trimmed Mean ( 4 / 32 )	1.26177528089888	0.0147290615290418	85.6656942067211
Trimmed Mean ( 5 / 32 )	1.26239425287356	0.0141382352583737	89.2893794595671
Trimmed Mean ( 6 / 32 )	1.26324	0.0137300592559125	92.0054295800667
Trimmed Mean ( 7 / 32 )	1.26324	0.0133469118171278	94.6466131872474
Trimmed Mean ( 8 / 32 )	1.26473827160494	0.0129387533469239	97.7480780175487
Trimmed Mean ( 9 / 32 )	1.26566962025316	0.0124829019517655	101.392258398229
Trimmed Mean ( 10 / 32 )	1.26654415584416	0.0120011255586148	105.535447459342
Trimmed Mean ( 11 / 32 )	1.267388	0.0114824227534213	110.376357604702
Trimmed Mean ( 12 / 32 )	1.26814246575342	0.0109657211008244	115.646062314870
Trimmed Mean ( 13 / 32 )	1.26838309859155	0.0105572584595029	120.143226904693
Trimmed Mean ( 14 / 32 )	1.26838309859155	0.0101370275628766	125.123769342068
Trimmed Mean ( 15 / 32 )	1.26871791044776	0.00972852351188358	130.412174971669
Trimmed Mean ( 16 / 32 )	1.26910923076923	0.00929697265736089	136.507794261868
Trimmed Mean ( 17 / 32 )	1.26906984126984	0.00891743737712319	142.313288851965
Trimmed Mean ( 18 / 32 )	1.26895901639344	0.00851604219916586	149.008070499901
Trimmed Mean ( 19 / 32 )	1.26882203389831	0.00817182944156054	155.267806673166
Trimmed Mean ( 20 / 32 )	1.26843333333333	0.00788865986524372	160.791991922717
Trimmed Mean ( 21 / 32 )	1.26808727272727	0.00764362019335333	165.901397590368
Trimmed Mean ( 22 / 32 )	1.268	0.00745153815663953	170.166209089351
Trimmed Mean ( 23 / 32 )	1.26801568627451	0.00725053635476418	174.885777304092
Trimmed Mean ( 24 / 32 )	1.26791836734694	0.00705866734152737	179.625743217498
Trimmed Mean ( 25 / 32 )	1.26791836734694	0.00691593919370417	183.332781251341
Trimmed Mean ( 26 / 32 )	1.26768666666667	0.00677912094655943	186.998679719684
Trimmed Mean ( 27 / 32 )	1.2675	0.00666571034115341	190.152277121102
Trimmed Mean ( 28 / 32 )	1.2675	0.00654462315240684	193.670433038435
Trimmed Mean ( 29 / 32 )	1.26711794871795	0.00638990946251996	198.299828213566
Trimmed Mean ( 30 / 32 )	1.26711891891892	0.00625025145180403	202.73087070012
Trimmed Mean ( 31 / 32 )	1.26711891891892	0.00613257454811886	206.621038028409
Trimmed Mean ( 32 / 32 )	1.26731212121212	0.00602248903664511	210.429959025395
Median	1.2694
Midrange	1.2235
Midmean - Weighted Average at Xnp	1.266175
Midmean - Weighted Average at X(n+1)p	1.26791836734694
Midmean - Empirical Distribution Function	1.26791836734694
Midmean - Empirical Distribution Function - Averaging	1.26791836734694
Midmean - Empirical Distribution Function - Interpolation	1.26791836734694
Midmean - Closest Observation	1.266132
Midmean - True Basic - Statistics Graphics Toolkit	1.26791836734694
Midmean - MS Excel (old versions)	1.26791836734694
Number of observations	97

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Mar/14/t1268599299oxy8ukx4jqvne3i/1lba71268599114.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Mar/14/t1268599299oxy8ukx4jqvne3i/1lba71268599114.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Mar/14/t1268599299oxy8ukx4jqvne3i/24gug1268599114.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Mar/14/t1268599299oxy8ukx4jqvne3i/24gug1268599114.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')

This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 License.

Software written by Ed van Stee & Patrick Wessa

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