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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: Mon, 02 Nov 2009 09:51:33 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Nov/02/t1257180847j58fugong5v70u8.htm/, Retrieved Mon, 02 Nov 2009 17:54:08 +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/2009/Nov/02/t1257180847j58fugong5v70u8.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:

KDGP1W52

Dataseries X:

» Textbox « » Textfile « » CSV «

100,7 100,9 101,8 102,9 103,2 104 105,3 105,9 105,9 106,3 106,4 106,5 106,9 107,7 109,4 109,6 110,7 110,9 110,9 111,9 112,2 112,8 113,2 113,4 113,5 113,5 113,9 114 114,1 114,8 114,9 115,1 115,2 115,3 115,3 115,4 115,4 115,5 115,8 115,8 116,2 116,3 116,8 116,9 117,3 118,2 118,7 118,9 119 119,4 119,5 119,6 119,7 119,8 120,1 120,2 120,2 120,5 120,6 120,9 121,3 121,3 121,5 121,6 121,7 121,8 121,9 122 122,5 122,6 123,1 124,2 124,3 124,3 124,3 124,4 124,8 124,8 125,1 125,2 125,6 125,8 126 126 126,5 126,5 127 128 129,1 129,7 130,7 131,3 131,5 131,9 135,2 137 137 137,1 138,8 141,1 143 143,3 143,3 144,2 146,5 148,6 151,7 157,8

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	'RServer@AstonUniversity' @ vre.aston.ac.uk

Central Tendency - Ungrouped Data
Measure	Value	S.E.	Value/S.E.
Arithmetic Mean	120.912962962963	1.09511809835598	110.410889149290
Geometric Mean	120.401632685974
Harmonic Mean	119.907755408857
Quadratic Mean	121.442447121931
Winsorized Mean ( 1 / 36 )	120.858333333333	1.07834912621388	112.077183905802
Winsorized Mean ( 2 / 36 )	120.817592592593	1.06080769261891	113.892078114855
Winsorized Mean ( 3 / 36 )	120.789814814815	1.04192650118815	115.929304684230
Winsorized Mean ( 4 / 36 )	120.715740740741	1.02116081236130	118.214231568093
Winsorized Mean ( 5 / 36 )	120.711111111111	1.00646949625436	119.935190843185
Winsorized Mean ( 6 / 36 )	120.783333333333	0.995615604877538	121.315227223854
Winsorized Mean ( 7 / 36 )	120.802777777778	0.985941731464081	122.525270939075
Winsorized Mean ( 8 / 36 )	120.662037037037	0.95707971876952	126.073131287504
Winsorized Mean ( 9 / 36 )	120.503703703704	0.91520172371727	131.669008679589
Winsorized Mean ( 10 / 36 )	120.355555555556	0.88521697450851	135.961644457145
Winsorized Mean ( 11 / 36 )	120.355555555556	0.881920374402736	136.469866270029
Winsorized Mean ( 12 / 36 )	120.4	0.87545468579944	137.528534546656
Winsorized Mean ( 13 / 36 )	120.279629629630	0.824089708588043	145.954534289369
Winsorized Mean ( 14 / 36 )	120.072222222222	0.724084785760698	165.826191329346
Winsorized Mean ( 15 / 36 )	120.044444444444	0.711848170722409	168.637708688103
Winsorized Mean ( 16 / 36 )	120.177777777778	0.68566306667788	175.272351127287
Winsorized Mean ( 17 / 36 )	120.114814814815	0.667438305785481	179.963921419608
Winsorized Mean ( 18 / 36 )	119.948148148148	0.64326997772805	186.466261913528
Winsorized Mean ( 19 / 36 )	120.018518518519	0.60579889003541	198.116108320211
Winsorized Mean ( 20 / 36 )	119.870370370370	0.570989041999817	209.934624928247
Winsorized Mean ( 21 / 36 )	119.792592592593	0.531196562810297	225.514622984060
Winsorized Mean ( 22 / 36 )	119.772222222222	0.508503041540588	235.538851172559
Winsorized Mean ( 23 / 36 )	119.814814814815	0.503394181874186	238.013904667576
Winsorized Mean ( 24 / 36 )	119.725925925926	0.487158335634109	245.763886540266
Winsorized Mean ( 25 / 36 )	119.725925925926	0.487158335634109	245.763886540266
Winsorized Mean ( 26 / 36 )	119.774074074074	0.469998803917912	254.83910400545
Winsorized Mean ( 27 / 36 )	119.749074074074	0.461121736738482	259.690802955983
Winsorized Mean ( 28 / 36 )	119.671296296296	0.445938656974118	268.358202243144
Winsorized Mean ( 29 / 36 )	119.832407407407	0.421336918303737	284.409939413431
Winsorized Mean ( 30 / 36 )	119.776851851852	0.408580109552052	293.153898223703
Winsorized Mean ( 31 / 36 )	119.834259259259	0.402220304659657	297.931899188079
Winsorized Mean ( 32 / 36 )	119.745370370370	0.385429018514452	310.680733982878
Winsorized Mean ( 33 / 36 )	119.745370370370	0.378626766366525	316.262295768208
Winsorized Mean ( 34 / 36 )	119.745370370370	0.378626766366525	316.262295768208
Winsorized Mean ( 35 / 36 )	119.777777777778	0.37508123807562	319.338227612519
Winsorized Mean ( 36 / 36 )	119.744444444444	0.371334242494877	322.470784379915
Trimmed Mean ( 1 / 36 )	120.755660377358	1.04210899591583	115.876228734822
Trimmed Mean ( 2 / 36 )	120.649038461538	1.00103101741147	120.524775319670
Trimmed Mean ( 3 / 36 )	120.559803921569	0.96516421019336	124.911183660049
Trimmed Mean ( 4 / 36 )	120.477	0.932645693658095	129.177672527984
Trimmed Mean ( 5 / 36 )	120.411224489796	0.902902119753974	133.360219070707
Trimmed Mean ( 6 / 36 )	120.34375	0.873334018640082	137.798078892420
Trimmed Mean ( 7 / 36 )	120.259574468085	0.842285458318196	142.777692859864
Trimmed Mean ( 8 / 36 )	120.168478260870	0.80889395761	148.559001004193
Trimmed Mean ( 9 / 36 )	120.094444444444	0.776983766279226	154.564933858973
Trimmed Mean ( 10 / 36 )	120.038636363636	0.749016128991561	160.261751005617
Trimmed Mean ( 11 / 36 )	119.998837209302	0.722699177901988	166.042581586521
Trimmed Mean ( 12 / 36 )	119.957142857143	0.692820914526222	173.143073977745
Trimmed Mean ( 13 / 36 )	119.908536585366	0.659106183566072	181.925977293378
Trimmed Mean ( 14 / 36 )	119.87	0.629248597510042	190.497047548981
Trimmed Mean ( 15 / 36 )	119.85	0.611801872996096	195.896752347413
Trimmed Mean ( 16 / 36 )	119.831578947368	0.593420683082314	201.933606905890
Trimmed Mean ( 17 / 36 )	119.8	0.576000971861453	207.985760185168
Trimmed Mean ( 18 / 36 )	119.772222222222	0.558436582921324	214.477750715512
Trimmed Mean ( 19 / 36 )	119.757142857143	0.541620035305368	221.109144881657
Trimmed Mean ( 20 / 36 )	119.735294117647	0.527520766772389	226.977403847514
Trimmed Mean ( 21 / 36 )	119.724242424242	0.516113594975658	231.972657937618
Trimmed Mean ( 22 / 36 )	119.71875	0.508327844427821	235.514838135134
Trimmed Mean ( 23 / 36 )	119.714516129032	0.50207842354106	238.437882442168
Trimmed Mean ( 24 / 36 )	119.706666666667	0.49501964046333	241.822054887809
Trimmed Mean ( 25 / 36 )	119.705172413793	0.488626991110376	244.982726275047
Trimmed Mean ( 26 / 36 )	119.703571428571	0.480529769107123	249.107504101138
Trimmed Mean ( 27 / 36 )	119.698148148148	0.473013819734649	253.054230456303
Trimmed Mean ( 28 / 36 )	119.694230769231	0.464845726541289	257.492376362847
Trimmed Mean ( 29 / 36 )	119.696	0.456892431407603	261.978513479066
Trimmed Mean ( 30 / 36 )	119.685416666667	0.450698724513147	265.555259327510
Trimmed Mean ( 31 / 36 )	119.678260869565	0.444612549598703	269.174275394574
Trimmed Mean ( 32 / 36 )	119.665909090909	0.437414361075438	273.575629288201
Trimmed Mean ( 33 / 36 )	119.659523809524	0.430838788681872	277.736190317533
Trimmed Mean ( 34 / 36 )	119.6525	0.422977654437969	282.881373861199
Trimmed Mean ( 35 / 36 )	119.644736842105	0.411908394994065	290.464429218125
Trimmed Mean ( 36 / 36 )	119.633333333333	0.39727244659729	301.136749749484
Median	119.95
Midrange	129.25
Midmean - Weighted Average at Xnp	119.592727272727
Midmean - Weighted Average at X(n+1)p	119.698148148148
Midmean - Empirical Distribution Function	119.592727272727
Midmean - Empirical Distribution Function - Averaging	119.698148148148
Midmean - Empirical Distribution Function - Interpolation	119.698148148148
Midmean - Closest Observation	119.592727272727
Midmean - True Basic - Statistics Graphics Toolkit	119.698148148148
Midmean - MS Excel (old versions)	119.703571428571
Number of observations	108

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Nov/02/t1257180847j58fugong5v70u8/10ejh1257180687.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Nov/02/t1257180847j58fugong5v70u8/10ejh1257180687.ps (open in new window)

http://www.freestatistics.org/blog/date/2009/Nov/02/t1257180847j58fugong5v70u8/2rajm1257180687.png (open in new window)

http://www.freestatistics.org/blog/date/2009/Nov/02/t1257180847j58fugong5v70u8/2rajm1257180687.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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