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TIJDREEKS A - STAP 14

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Sun, 15 Aug 2010 18:11:00 +0000

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Aug/15/t12818961584o11iqi69a83zib.htm/, Retrieved Sun, 15 Aug 2010 20:16:00 +0200

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/Aug/15/t12818961584o11iqi69a83zib.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:

De Cock Nicola

Dataseries X:

» Textbox « » Textfile « » CSV «

252 251 250 248 268 267 252 242 243 243 244 246 236 241 240 239 253 249 232 229 221 222 224 224 215 225 225 221 238 234 228 227 216 219 225 227 205 215 214 209 222 216 206 199 189 198 203 211 199 211 210 203 214 202 193 193 176 192 200 195 180 197 194 194 212 202 195 198 170 187 190 189 176 188 195 194 211 203 194 194 163 183 181 184 171 178 179 186 205 204 195 186 156 167 164 165 153 160 154 169 186 188 187 169 131 146 145 137 119 118 113 123 142 141 138 124 83 100 96 98

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	195.341666666667	3.54047219930114	55.1739021436817
Geometric Mean	190.884230416638
Harmonic Mean	185.584928714322
Quadratic Mean	199.123140292634
Winsorized Mean ( 1 / 40 )	195.441666666667	3.51170104569857	55.6544148044892
Winsorized Mean ( 2 / 40 )	195.241666666667	3.46747585026566	56.3065685523689
Winsorized Mean ( 3 / 40 )	195.266666666667	3.45231082706719	56.5611488790973
Winsorized Mean ( 4 / 40 )	195.7	3.35714047320971	58.2936584160549
Winsorized Mean ( 5 / 40 )	195.866666666667	3.30911933525774	59.1899677294082
Winsorized Mean ( 6 / 40 )	195.866666666667	3.29231626749751	59.492056884178
Winsorized Mean ( 7 / 40 )	196.041666666667	3.23927655221028	60.5202005777802
Winsorized Mean ( 8 / 40 )	196.041666666667	3.21758551701278	60.9281915368244
Winsorized Mean ( 9 / 40 )	196.416666666667	3.10135922432117	63.3324463436379
Winsorized Mean ( 10 / 40 )	196.75	2.99280767158594	65.7409434852654
Winsorized Mean ( 11 / 40 )	196.75	2.96539920364439	66.34857113275
Winsorized Mean ( 12 / 40 )	197.05	2.91619283866292	67.5709772644349
Winsorized Mean ( 13 / 40 )	197.05	2.88449078952351	68.3136173343618
Winsorized Mean ( 14 / 40 )	197.283333333333	2.81383594684569	70.1118818083506
Winsorized Mean ( 15 / 40 )	197.283333333333	2.77814558722688	71.0125971224783
Winsorized Mean ( 16 / 40 )	198.083333333333	2.62079550791442	75.5813770037192
Winsorized Mean ( 17 / 40 )	198.083333333333	2.58189622989063	76.7200986004478
Winsorized Mean ( 18 / 40 )	198.083333333333	2.50054849258561	79.2159535880513
Winsorized Mean ( 19 / 40 )	198.4	2.37250237239140	83.6247846614459
Winsorized Mean ( 20 / 40 )	198.566666666667	2.26376070106169	87.7153961430374
Winsorized Mean ( 21 / 40 )	198.216666666667	2.17685119820403	91.056599013383
Winsorized Mean ( 22 / 40 )	198.216666666667	2.13107537632307	93.0125085526855
Winsorized Mean ( 23 / 40 )	198.408333333333	2.05895243527357	96.363728435024
Winsorized Mean ( 24 / 40 )	198.808333333333	2.00836122811503	98.9903263169083
Winsorized Mean ( 25 / 40 )	198.391666666667	1.96000971219416	101.219736531088
Winsorized Mean ( 26 / 40 )	198.608333333333	1.93288277735590	102.752394330411
Winsorized Mean ( 27 / 40 )	198.833333333333	1.90507700474922	104.370234293761
Winsorized Mean ( 28 / 40 )	199.766666666667	1.73914131446278	114.865114758299
Winsorized Mean ( 29 / 40 )	199.766666666667	1.73914131446278	114.865114758299
Winsorized Mean ( 30 / 40 )	199.766666666667	1.62420992787958	122.993132376345
Winsorized Mean ( 31 / 40 )	200.025	1.59535664198512	125.379488658477
Winsorized Mean ( 32 / 40 )	200.025	1.5352288171502	130.290024369983
Winsorized Mean ( 33 / 40 )	200.3	1.50534063260382	133.059585094396
Winsorized Mean ( 34 / 40 )	200.3	1.37990784411978	145.154620907143
Winsorized Mean ( 35 / 40 )	199.716666666667	1.25139604581925	159.595091684917
Winsorized Mean ( 36 / 40 )	200.316666666667	1.18935423321376	168.424730893999
Winsorized Mean ( 37 / 40 )	200.008333333333	1.15545811263182	173.098731270984
Winsorized Mean ( 38 / 40 )	200.008333333333	1.15545811263182	173.098731270984
Winsorized Mean ( 39 / 40 )	200.008333333333	1.08726366332003	183.955686261596
Winsorized Mean ( 40 / 40 )	200.008333333333	1.08726366332003	183.955686261596
Trimmed Mean ( 1 / 40 )	195.677966101695	3.41581738325692	57.2858394189445
Trimmed Mean ( 2 / 40 )	195.922413793103	3.30888927816915	59.2109307149467
Trimmed Mean ( 3 / 40 )	196.280701754386	3.21552834519078	61.0415087921549
Trimmed Mean ( 4 / 40 )	196.642857142857	3.11726151616712	63.0819249918572
Trimmed Mean ( 5 / 40 )	196.9	3.03905493189345	64.7898785683758
Trimmed Mean ( 6 / 40 )	197.129629629630	2.96483639717143	66.4892099333706
Trimmed Mean ( 7 / 40 )	197.367924528302	2.88557852554382	68.3980431588171
Trimmed Mean ( 8 / 40 )	197.586538461538	2.80817549705826	70.3611788752245
Trimmed Mean ( 9 / 40 )	197.813725490196	2.72522568895638	72.5861811342121
Trimmed Mean ( 10 / 40 )	198	2.6537946911218	74.6101424734941
Trimmed Mean ( 11 / 40 )	198.15306122449	2.59234465254196	76.4377765241163
Trimmed Mean ( 12 / 40 )	198.3125	2.52727717795467	78.4688366317202
Trimmed Mean ( 13 / 40 )	198.446808510638	2.46149096617165	80.6205715307914
Trimmed Mean ( 14 / 40 )	198.586956521739	2.3915139116791	83.0381774289198
Trimmed Mean ( 15 / 40 )	198.711111111111	2.32262091208070	85.5546895653745
Trimmed Mean ( 16 / 40 )	198.840909090909	2.24904986113179	88.4110719496659
Trimmed Mean ( 17 / 40 )	198.906976744186	2.18849296990806	90.8876471065576
Trimmed Mean ( 18 / 40 )	198.976190476190	2.12442670140921	93.6611229487007
Trimmed Mean ( 19 / 40 )	199.048780487805	2.06225761865593	96.5198424712497
Trimmed Mean ( 20 / 40 )	199.1	2.00873094266007	99.1173062412935
Trimmed Mean ( 21 / 40 )	199.141025641026	1.96181703027181	101.508460049118
Trimmed Mean ( 22 / 40 )	199.210526315789	1.91891012464940	103.814412023172
Trimmed Mean ( 23 / 40 )	199.283783783784	1.87488321445704	106.291305104833
Trimmed Mean ( 24 / 40 )	199.347222222222	1.83313696368547	108.746496400051
Trimmed Mean ( 25 / 40 )	199.385714285714	1.79097031858340	111.328318630887
Trimmed Mean ( 26 / 40 )	199.455882352941	1.74749712194023	114.138031959382
Trimmed Mean ( 27 / 40 )	199.515151515152	1.69961498783487	117.388439701460
Trimmed Mean ( 28 / 40 )	199.5625	1.64643599574816	121.208780976218
Trimmed Mean ( 29 / 40 )	199.548387096774	1.60786627569773	124.107576676537
Trimmed Mean ( 30 / 40 )	199.533333333333	1.56090417565409	127.831891569974
Trimmed Mean ( 31 / 40 )	199.517241379310	1.52181979835832	131.104380160215
Trimmed Mean ( 32 / 40 )	199.482142857143	1.47819455326127	134.949856510454
Trimmed Mean ( 33 / 40 )	199.444444444444	1.43424880974837	139.058469554830
Trimmed Mean ( 34 / 40 )	199.384615384615	1.38434302667389	144.028330798667
Trimmed Mean ( 35 / 40 )	199.32	1.34450962155314	148.247358594393
Trimmed Mean ( 36 / 40 )	199.291666666667	1.31748953100304	151.266224115603
Trimmed Mean ( 37 / 40 )	199.217391304348	1.29283160874803	154.093843278838
Trimmed Mean ( 38 / 40 )	199.159090909091	1.26672455620301	157.223675765841
Trimmed Mean ( 39 / 40 )	199.095238095238	1.23151112702747	161.667429327901
Trimmed Mean ( 40 / 40 )	199.025	1.19908485403640	165.980747175678
Median	198
Midrange	175.5
Midmean - Weighted Average at Xnp	198.774193548387
Midmean - Weighted Average at X(n+1)p	199.533333333333
Midmean - Empirical Distribution Function	198.774193548387
Midmean - Empirical Distribution Function - Averaging	199.533333333333
Midmean - Empirical Distribution Function - Interpolation	199.533333333333
Midmean - Closest Observation	198.774193548387
Midmean - True Basic - Statistics Graphics Toolkit	199.533333333333
Midmean - MS Excel (old versions)	199.5625
Number of observations	120

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Aug/15/t12818961584o11iqi69a83zib/19t3b1281895858.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Aug/15/t12818961584o11iqi69a83zib/19t3b1281895858.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Aug/15/t12818961584o11iqi69a83zib/29t3b1281895858.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Aug/15/t12818961584o11iqi69a83zib/29t3b1281895858.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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