Home » date » 2009 » Mar » 23 »

Centrummaten - Aantal Nieuwe Gebouwen - Morre Christophe

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Mon, 23 Mar 2009 10:03:38 -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/Mar/23/t1237824256oaqynlwvdtiqkzw.htm/, Retrieved Mon, 23 Mar 2009 17:04:18 +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/Mar/23/t1237824256oaqynlwvdtiqkzw.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:

Dataseries X:

» Textbox « » Textfile « » CSV «

2194 2419 2742 2137 2710 2173 2363 2126 1905 2121 1983 1734 2074 2049 2406 2558 2251 2059 2397 1747 1707 2319 1631 1627 1791 2034 1997 2169 2028 2253 2218 1855 2187 1852 1570 1851 1954 1828 2251 2277 2085 2282 2266 1878 2267 2069 1746 2299 2360 2214 2825 2355 2333 3016 2155 2172 2150 2533 2058 2160 2260 2498 2695 2799 2945 2930 2318 2540 2570 2669 2450 2842 3440 2678 2981 2259 2844 2546 2456 2295 2379 2479 2057 2280 2351 2275 2543 2305 2188 2720 2398 2147 1898 2538 2081 2057 2497 2460 2195 2823 2100 2640 2342 2171 2482

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	'George Udny Yule' @ 72.249.76.132

Central Tendency - Ungrouped Data
Measure	Value	S.E.	Value/S.E.
Arithmetic Mean	2287.53333333333	32.9677055507296	69.3870954960257
Geometric Mean	2263.14545703274
Harmonic Mean	2238.91388342336
Quadratic Mean	2312.10795389752
Winsorized Mean ( 1 / 35 )	2284.03809523810	31.7257995907443	71.9930821193373
Winsorized Mean ( 2 / 35 )	2283.44761904762	31.565859347797	72.3391558546934
Winsorized Mean ( 3 / 35 )	2284.59047619048	30.9401190984105	73.8390976752201
Winsorized Mean ( 4 / 35 )	2285.04761904762	30.6423937850444	74.5714461826048
Winsorized Mean ( 5 / 35 )	2281.52380952381	29.7563583110185	76.673488928885
Winsorized Mean ( 6 / 35 )	2281.46666666667	29.7257275214397	76.7505745661282
Winsorized Mean ( 7 / 35 )	2283.26666666667	29.0283973212069	78.656311659294
Winsorized Mean ( 8 / 35 )	2285.93333333333	28.553648710819	80.0574860496618
Winsorized Mean ( 9 / 35 )	2285.84761904762	27.8857256700471	81.9719610704955
Winsorized Mean ( 10 / 35 )	2280.51428571429	26.9434427121059	84.640790343011
Winsorized Mean ( 11 / 35 )	2278.52380952381	26.5210024425252	85.9139398845008
Winsorized Mean ( 12 / 35 )	2280.00952380952	25.9407379535499	87.8930093620376
Winsorized Mean ( 13 / 35 )	2280.62857142857	25.2816560970172	90.2088281984677
Winsorized Mean ( 14 / 35 )	2279.29523809524	24.7921023250158	91.9363436071083
Winsorized Mean ( 15 / 35 )	2285.00952380952	23.6114320701346	96.7755584253512
Winsorized Mean ( 16 / 35 )	2285.00952380952	22.3428352834896	102.270347286589
Winsorized Mean ( 17 / 35 )	2275.94285714286	20.3914432449941	111.612642116520
Winsorized Mean ( 18 / 35 )	2279.2	19.4265282539109	117.324102907639
Winsorized Mean ( 19 / 35 )	2278.11428571429	18.9948629757166	119.933178176998
Winsorized Mean ( 20 / 35 )	2280.4	18.5695041268334	122.803494612695
Winsorized Mean ( 21 / 35 )	2281.4	18.2977390064252	124.682071331267
Winsorized Mean ( 22 / 35 )	2280.98095238095	18.2408790040693	125.047754106153
Winsorized Mean ( 23 / 35 )	2280.10476190476	18.0671008345514	126.202027806493
Winsorized Mean ( 24 / 35 )	2272.33333333333	16.9897225271831	133.747524698986
Winsorized Mean ( 25 / 35 )	2274.47619047619	16.6744254572480	136.405071125705
Winsorized Mean ( 26 / 35 )	2272	16.0557122992378	141.507269042673
Winsorized Mean ( 27 / 35 )	2273.02857142857	15.7464250093669	144.352039912326
Winsorized Mean ( 28 / 35 )	2269.02857142857	14.9918198521853	151.351109725203
Winsorized Mean ( 29 / 35 )	2272.06666666667	14.3731362331624	158.077306845840
Winsorized Mean ( 30 / 35 )	2276.35238095238	13.4834451537699	168.825723321604
Winsorized Mean ( 31 / 35 )	2268.67619047619	12.2091097859434	185.818313558632
Winsorized Mean ( 32 / 35 )	2268.06666666667	11.3691332869833	199.493365889501
Winsorized Mean ( 33 / 35 )	2268.69523809524	10.7311733414290	211.411666358670
Winsorized Mean ( 34 / 35 )	2269.34285714286	10.5880386290105	214.33080636153
Winsorized Mean ( 35 / 35 )	2265.00952380952	9.7205881659852	233.011571433030
Trimmed Mean ( 1 / 35 )	2283.31067961165	30.8884652142306	73.9211438242555
Trimmed Mean ( 2 / 35 )	2282.55445544554	29.9440252565327	76.2273754410348
Trimmed Mean ( 3 / 35 )	2282.08080808081	28.9721881891917	78.7679823553043
Trimmed Mean ( 4 / 35 )	2281.17525773196	28.1393959350367	81.0669590419898
Trimmed Mean ( 5 / 35 )	2280.10526315789	27.2949895671786	83.5356708067643
Trimmed Mean ( 6 / 35 )	2279.78494623656	26.5908994750213	85.7355332555832
Trimmed Mean ( 7 / 35 )	2279.46153846154	25.7957285448206	88.3658522960857
Trimmed Mean ( 8 / 35 )	2278.8202247191	25.0473074454122	90.9806465100303
Trimmed Mean ( 9 / 35 )	2277.74712643678	24.2890694122660	93.7766321045845
Trimmed Mean ( 10 / 35 )	2276.63529411765	23.5508559144289	96.6688982510746
Trimmed Mean ( 11 / 35 )	2276.14457831325	22.8811153587789	99.4769941335032
Trimmed Mean ( 12 / 35 )	2275.86419753086	22.1835549219977	102.592402594323
Trimmed Mean ( 13 / 35 )	2275.40506329114	21.4762197918758	105.949980273153
Trimmed Mean ( 14 / 35 )	2274.85714285714	20.7661252950461	109.546538438725
Trimmed Mean ( 15 / 35 )	2274.41333333333	20.0190728276031	113.612321255822
Trimmed Mean ( 16 / 35 )	2273.39726027397	19.3393426706753	117.552974730686
Trimmed Mean ( 17 / 35 )	2272.32394366197	18.7485079180739	121.200255166514
Trimmed Mean ( 18 / 35 )	2272	18.3654643646689	123.710457567892
Trimmed Mean ( 19 / 35 )	2271.37313432836	18.0531883624516	125.815622632761
Trimmed Mean ( 20 / 35 )	2270.8	17.7416041898913	127.992935458105
Trimmed Mean ( 21 / 35 )	2270	17.4258137880305	130.266513094454
Trimmed Mean ( 22 / 35 )	2269.06557377049	17.0804088210191	132.846092710509
Trimmed Mean ( 23 / 35 )	2268.10169491525	16.6654553509498	136.095993007835
Trimmed Mean ( 24 / 35 )	2267.14035087719	16.1839643127076	140.085599984735
Trimmed Mean ( 25 / 35 )	2266.72727272727	15.7785912696556	143.658406126946
Trimmed Mean ( 26 / 35 )	2266.11320754717	15.3252275102823	147.868160914854
Trimmed Mean ( 27 / 35 )	2266.11320754717	14.8687809152405	152.407465041361
Trimmed Mean ( 28 / 35 )	2265.06122448980	14.3469641768289	157.877387618210
Trimmed Mean ( 29 / 35 )	2264.74468085106	13.8329022322698	163.721585161485
Trimmed Mean ( 30 / 35 )	2264.15555555556	13.2946771286522	170.305418751083
Trimmed Mean ( 31 / 35 )	2263.16279069767	12.7781968510717	177.111279241865
Trimmed Mean ( 32 / 35 )	2262.70731707317	12.3905079672264	182.616186766366
Trimmed Mean ( 33 / 35 )	2262.25641025641	12.0569229052975	187.631324179938
Trimmed Mean ( 34 / 35 )	2261.70270270270	11.7441356437720	192.581452676093
Trimmed Mean ( 35 / 35 )	2261.02857142857	11.3358571207768	199.458104256138
Median	2266
Midrange	2505
Midmean - Weighted Average at Xnp	2261.96153846154
Midmean - Weighted Average at X(n+1)p	2266.11320754717
Midmean - Empirical Distribution Function	2266.11320754717
Midmean - Empirical Distribution Function - Averaging	2266.11320754717
Midmean - Empirical Distribution Function - Interpolation	2266.11320754717
Midmean - Closest Observation	2262.46296296296
Midmean - True Basic - Statistics Graphics Toolkit	2266.11320754717
Midmean - MS Excel (old versions)	2266.11320754717
Number of observations	105

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Mar/23/t1237824256oaqynlwvdtiqkzw/1kf981237824216.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Mar/23/t1237824256oaqynlwvdtiqkzw/1kf981237824216.ps (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Mar/23/t1237824256oaqynlwvdtiqkzw/2sh2m1237824216.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Mar/23/t1237824256oaqynlwvdtiqkzw/2sh2m1237824216.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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