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Central tendency: prijs ruwe olie per barrel

*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: Fri, 12 Dec 2008 06:03:33 -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/12/t1229087120cwx6cjc2u3esi5g.htm/, Retrieved Fri, 12 Dec 2008 14:05:22 +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/12/t1229087120cwx6cjc2u3esi5g.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},
}

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

Dataseries X:

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32.68 31.54 32.43 26.54 25.85 27.6 25.71 25.38 28.57 27.64 25.36 25.9 26.29 21.74 19.2 19.32 19.82 20.36 24.31 25.97 25.61 24.67 25.59 26.09 28.37 27.34 24.46 27.46 30.23 32.33 29.87 24.87 25.48 27.28 28.24 29.58 26.95 29.08 28.76 29.59 30.7 30.52 32.67 33.19 37.13 35.54 37.75 41.84 42.94 49.14 44.61 40.22 44.23 45.85 53.38 53.26 51.8 55.3 57.81 63.96 63.77 59.15 56.12 57.42 63.52 61.71 63.01 68.18 72.03 69.75 74.41 74.33 64.24 60.03 59.44 62.5 55.04 58.34 61.92 67.65 67.68 70.3 75.26 71.44 76.36 81.71 92.6 90.6 92.23 94.09 102.79 109.65 124.05 132.69 135.81 116.07 101.42 75.73 55.48

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	'George Udny Yule' @ 72.249.76.132

Central Tendency - Ungrouped Data
Measure	Value	S.E.	Value/S.E.
Arithmetic Mean	50.3476767676768	2.75381043268426	18.2829130756836
Geometric Mean	44.0438528677522
Harmonic Mean	39.0194688395435
Quadratic Mean	57.2544216809514
Winsorized Mean ( 1 / 33 )	50.3173737373737	2.74385319511376	18.3382164275329
Winsorized Mean ( 2 / 33 )	50.1529292929293	2.69148299842842	18.6339387327411
Winsorized Mean ( 3 / 33 )	49.9274747474747	2.62460026638462	19.0228871752153
Winsorized Mean ( 4 / 33 )	49.7238383838384	2.55383910223663	19.4702314410844
Winsorized Mean ( 5 / 33 )	49.5071717171717	2.45996417626635	20.1251596241991
Winsorized Mean ( 6 / 33 )	49.4332323232323	2.44081549252888	20.2527526044238
Winsorized Mean ( 7 / 33 )	48.929797979798	2.33159799848667	20.9855206650357
Winsorized Mean ( 8 / 33 )	48.8255555555556	2.30632425857646	21.1702909397885
Winsorized Mean ( 9 / 33 )	48.8364646464646	2.29513682983814	21.2782366661375
Winsorized Mean ( 10 / 33 )	48.6738383838384	2.26348099422908	21.5039748546315
Winsorized Mean ( 11 / 33 )	47.6971717171717	2.08632917580535	22.8617671028639
Winsorized Mean ( 12 / 33 )	47.0620202020202	1.98188938347742	23.7460377932119
Winsorized Mean ( 13 / 33 )	46.9819191919192	1.96919715862363	23.858413052331
Winsorized Mean ( 14 / 33 )	46.929595959596	1.95777431023822	23.9708916978718
Winsorized Mean ( 15 / 33 )	46.8220202020202	1.93655933259108	24.1779425055742
Winsorized Mean ( 16 / 33 )	46.8171717171717	1.93378862508657	24.2100771045108
Winsorized Mean ( 17 / 33 )	46.4342424242424	1.87628091114648	24.7480226166504
Winsorized Mean ( 18 / 33 )	46.3487878787879	1.85899993325981	24.9321084146108
Winsorized Mean ( 19 / 33 )	46.1683838383838	1.82490239264271	25.2990976528480
Winsorized Mean ( 20 / 33 )	46.1077777777778	1.8043764883071	25.553302249597
Winsorized Mean ( 21 / 33 )	45.8617171717172	1.75083977283187	26.1941257466060
Winsorized Mean ( 22 / 33 )	45.8239393939394	1.72838872311578	26.5125193083487
Winsorized Mean ( 23 / 33 )	45.8309090909091	1.72596455360448	26.5537950910965
Winsorized Mean ( 24 / 33 )	45.0333333333333	1.61931482388886	27.8101161484977
Winsorized Mean ( 25 / 33 )	44.9979797979798	1.60686833621292	28.0035263524025
Winsorized Mean ( 26 / 33 )	44.9585858585859	1.59970972430072	28.1042148932605
Winsorized Mean ( 27 / 33 )	45.0540404040404	1.57357645364852	28.6316183109994
Winsorized Mean ( 28 / 33 )	44.9465656565657	1.55236888265576	28.9535342783167
Winsorized Mean ( 29 / 33 )	44.8557575757576	1.52832253837367	29.3496670038575
Winsorized Mean ( 30 / 33 )	44.7375757575758	1.50145100636989	29.7962274944551
Winsorized Mean ( 31 / 33 )	44.7720202020202	1.48292929103369	30.1916082396696
Winsorized Mean ( 32 / 33 )	44.3906060606061	1.40294715723665	31.6409679663497
Winsorized Mean ( 33 / 33 )	44.1972727272727	1.38032090217995	32.0195634634465
Trimmed Mean ( 1 / 33 )	49.7877319587629	2.64750508042646	18.8055283923169
Trimmed Mean ( 2 / 33 )	49.2357894736842	2.53619785605106	19.4132288836273
Trimmed Mean ( 3 / 33 )	48.7476344086022	2.44040274420984	19.9752415966020
Trimmed Mean ( 4 / 33 )	48.3197802197802	2.35963723634189	20.4776308305296
Trimmed Mean ( 5 / 33 )	47.9293258426966	2.29133111059261	20.9176777730306
Trimmed Mean ( 6 / 33 )	47.5702298850575	2.23997269607249	21.2369686329060
Trimmed Mean ( 7 / 33 )	47.2085882352941	2.185250110056	21.6032883458289
Trimmed Mean ( 8 / 33 )	46.9153012048193	2.14733454452646	21.8481565084519
Trimmed Mean ( 9 / 33 )	46.6234567901235	2.10828724265602	22.1143759952687
Trimmed Mean ( 10 / 33 )	46.3153164556962	2.06449083068566	22.4342563150614
Trimmed Mean ( 11 / 33 )	46.0120779220779	2.01907754681269	22.7886630678017
Trimmed Mean ( 12 / 33 )	45.8098666666667	1.99809470050651	22.9267745192728
Trimmed Mean ( 13 / 33 )	45.6683561643836	1.98999146237067	22.9490211530752
Trimmed Mean ( 14 / 33 )	45.5274647887324	1.98113119037921	22.9805401125495
Trimmed Mean ( 15 / 33 )	45.383768115942	1.97104342805725	23.0252502151483
Trimmed Mean ( 16 / 33 )	45.2420895522388	1.96089322516388	23.0721841310140
Trimmed Mean ( 17 / 33 )	45.0921538461538	1.94771549479605	23.1513041646134
Trimmed Mean ( 18 / 33 )	44.9680952380952	1.93923855624859	23.1885319592062
Trimmed Mean ( 19 / 33 )	44.843606557377	1.92984854629261	23.2368527797299
Trimmed Mean ( 20 / 33 )	44.7266101694915	1.92175421230027	23.2738452624258
Trimmed Mean ( 21 / 33 )	44.6066666666667	1.91290463855988	23.3188135819717
Trimmed Mean ( 22 / 33 )	44.4990909090909	1.90799163316759	23.3224769624460
Trimmed Mean ( 23 / 33 )	44.3866037735849	1.90270994854368	23.3280978046906
Trimmed Mean ( 24 / 33 )	44.2647058823529	1.89374935403737	23.3741100890585
Trimmed Mean ( 25 / 33 )	44.2	1.89694249157072	23.3006536552414
Trimmed Mean ( 26 / 33 )	44.1327659574468	1.89907046014432	23.2391408763701
Trimmed Mean ( 27 / 33 )	44.1327659574468	1.89887435082590	23.241540936214
Trimmed Mean ( 28 / 33 )	43.9783720930233	1.89860399056322	23.1635308424571
Trimmed Mean ( 29 / 33 )	43.8948780487805	1.89736226152453	23.134684893285
Trimmed Mean ( 30 / 33 )	43.8107692307692	1.89514164649294	23.1174114672871
Trimmed Mean ( 31 / 33 )	43.7281081081081	1.89197212828569	23.1124483571172
Trimmed Mean ( 32 / 33 )	43.6328571428571	1.88531229481473	23.1435700402860
Trimmed Mean ( 33 / 33 )	43.5618181818182	1.88776545667662	23.0758635972225
Median	42.94
Midrange	77.505
Midmean - Weighted Average at Xnp	43.8652
Midmean - Weighted Average at X(n+1)p	44.2647058823529
Midmean - Empirical Distribution Function	44.2647058823529
Midmean - Empirical Distribution Function - Averaging	44.2647058823529
Midmean - Empirical Distribution Function - Interpolation	44.2
Midmean - Closest Observation	43.8652
Midmean - True Basic - Statistics Graphics Toolkit	44.2647058823529
Midmean - MS Excel (old versions)	44.2647058823529
Number of observations	99

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/12/t1229087120cwx6cjc2u3esi5g/1ybhp1229087010.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/12/t1229087120cwx6cjc2u3esi5g/1ybhp1229087010.ps (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/12/t1229087120cwx6cjc2u3esi5g/29yue1229087010.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/Dec/12/t1229087120cwx6cjc2u3esi5g/29yue1229087010.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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