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Tijdreeks 2 - Stap 9

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Tue, 20 Jul 2010 11:06:17 +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/Jul/20/t1279624487ce37l5paf5jcqvk.htm/, Retrieved Tue, 20 Jul 2010 13:14:49 +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/Jul/20/t1279624487ce37l5paf5jcqvk.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:

Van Puyenbroeck Cassandra

Dataseries X:

» Textbox « » Textfile « » CSV «

349 348 347 345 365 364 349 339 340 340 341 343 341 343 341 335 355 357 337 325 336 338 337 328 326 327 319 310 320 322 303 292 303 315 311 307 308 312 309 310 309 304 287 275 290 298 294 286 294 292 287 281 280 271 264 259 271 279 279 273 286 286 280 277 269 255 252 245 257 267 261 258 271 262 258 253 236 228 235 226 231 235 227 222 233 221 218 220 204 196 208 190 191 194 179 162 179 176 168 170 153 142 155 136 136 144 135 114 135 132 123 123 103 97 113 108 111 121 111 97

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	'Gwilym Jenkins' @ 72.249.127.135

Central Tendency - Ungrouped Data
Measure	Value	S.E.	Value/S.E.
Arithmetic Mean	254.875	6.92389159793421	36.8109460402360
Geometric Mean	241.070059591576
Harmonic Mean	224.583816220851
Quadratic Mean	265.831071045755
Winsorized Mean ( 1 / 40 )	254.866666666667	6.92278272336498	36.8156385735566
Winsorized Mean ( 2 / 40 )	254.85	6.88894142852167	36.9940726952427
Winsorized Mean ( 3 / 40 )	254.925	6.85993485628639	37.161431608405
Winsorized Mean ( 4 / 40 )	254.825	6.81820415601977	37.3742108873369
Winsorized Mean ( 5 / 40 )	254.825	6.81820415601977	37.3742108873369
Winsorized Mean ( 6 / 40 )	254.875	6.79478670751041	37.5103753762103
Winsorized Mean ( 7 / 40 )	254.875	6.77788423004217	37.6039175868919
Winsorized Mean ( 8 / 40 )	255.208333333333	6.68259891568945	38.1899821541217
Winsorized Mean ( 9 / 40 )	255.208333333333	6.64059217257224	38.4315625325442
Winsorized Mean ( 10 / 40 )	255.208333333333	6.64059217257224	38.4315625325442
Winsorized Mean ( 11 / 40 )	255.85	6.48504690294013	39.4522975437549
Winsorized Mean ( 12 / 40 )	256.15	6.43724989995804	39.7918371945867
Winsorized Mean ( 13 / 40 )	256.15	6.43724989995804	39.7918371945867
Winsorized Mean ( 14 / 40 )	256.15	6.40595234841753	39.9862481123946
Winsorized Mean ( 15 / 40 )	256.15	6.40595234841753	39.9862481123946
Winsorized Mean ( 16 / 40 )	256.816666666667	6.26662476146666	40.981657023064
Winsorized Mean ( 17 / 40 )	256.958333333333	6.20757190826374	41.394338580478
Winsorized Mean ( 18 / 40 )	258.158333333333	5.9881535225569	43.1115088083282
Winsorized Mean ( 19 / 40 )	258.475	5.94161559412483	43.5024777192898
Winsorized Mean ( 20 / 40 )	259.475	5.75461040960955	45.0899333804954
Winsorized Mean ( 21 / 40 )	260.35	5.58733373974812	46.5964648125237
Winsorized Mean ( 22 / 40 )	259.433333333333	5.39571016103751	48.0814064489054
Winsorized Mean ( 23 / 40 )	260.391666666667	5.21690980138789	49.9130091529267
Winsorized Mean ( 24 / 40 )	260.791666666667	5.1143629221934	50.9920141832290
Winsorized Mean ( 25 / 40 )	260.583333333333	5.09212858990198	51.1737535163756
Winsorized Mean ( 26 / 40 )	262.316666666667	4.70846105525682	55.7117630555316
Winsorized Mean ( 27 / 40 )	262.091666666667	4.63182263574916	56.5849962914816
Winsorized Mean ( 28 / 40 )	262.558333333333	4.51753192069835	58.1198623368544
Winsorized Mean ( 29 / 40 )	262.075	4.35578372864819	60.1671286561637
Winsorized Mean ( 30 / 40 )	263.325	4.02802094471869	65.3732946312647
Winsorized Mean ( 31 / 40 )	264.1	3.87494284768552	68.1558439391553
Winsorized Mean ( 32 / 40 )	266.5	3.53109437016067	75.4723527787998
Winsorized Mean ( 33 / 40 )	267.05	3.46799795327529	77.004082354717
Winsorized Mean ( 34 / 40 )	267.05	3.40634705808320	78.3977661249448
Winsorized Mean ( 35 / 40 )	267.341666666667	3.373307145385	79.2520974653657
Winsorized Mean ( 36 / 40 )	268.241666666667	3.20792077816056	83.6185446014905
Winsorized Mean ( 37 / 40 )	268.241666666667	3.14181600667426	85.3779044020504
Winsorized Mean ( 38 / 40 )	267.608333333333	3.00930619681367	88.926920635954
Winsorized Mean ( 39 / 40 )	268.258333333333	2.86912219355176	93.4983995928208
Winsorized Mean ( 40 / 40 )	268.925	2.79676089407004	96.1558782412185
Trimmed Mean ( 1 / 40 )	255.279661016949	6.84843346596433	37.275628402561
Trimmed Mean ( 2 / 40 )	255.706896551724	6.76563121248529	37.7949800278565
Trimmed Mean ( 3 / 40 )	256.157894736842	6.69273252691421	38.2740373542087
Trimmed Mean ( 4 / 40 )	256.598214285714	6.62274535857513	38.7449917508109
Trimmed Mean ( 5 / 40 )	257.081818181818	6.55708406452299	39.2067290356632
Trimmed Mean ( 6 / 40 )	257.583333333333	6.4830519656943	39.7318014256805
Trimmed Mean ( 7 / 40 )	258.094339622641	6.40495552056881	40.296039339196
Trimmed Mean ( 8 / 40 )	258.625	6.320231799842	40.9201763780982
Trimmed Mean ( 9 / 40 )	259.127450980392	6.24258319887530	41.5096511692593
Trimmed Mean ( 10 / 40 )	259.65	6.16174865315411	42.1390119292011
Trimmed Mean ( 11 / 40 )	260.193877551020	6.06980673414506	42.8669130579277
Trimmed Mean ( 12 / 40 )	260.6875	5.99011086540346	43.5196452716141
Trimmed Mean ( 13 / 40 )	261.170212765957	5.90639712090779	44.2181938362141
Trimmed Mean ( 14 / 40 )	261.673913043478	5.81049490989042	45.0347030849414
Trimmed Mean ( 15 / 40 )	262.2	5.70498610138349	45.9597964553174
Trimmed Mean ( 16 / 40 )	262.75	5.58367643481744	47.0568098039496
Trimmed Mean ( 17 / 40 )	263.267441860465	5.46443355167376	48.1783590871603
Trimmed Mean ( 18 / 40 )	263.797619047619	5.33506622813693	49.445987691092
Trimmed Mean ( 19 / 40 )	264.256097560976	5.21722678031237	50.6506825730036
Trimmed Mean ( 20 / 40 )	264.7125	5.08700235491009	52.0370311494929
Trimmed Mean ( 21 / 40 )	265.115384615385	4.96242896391022	53.4245198356417
Trimmed Mean ( 22 / 40 )	265.473684210526	4.84092472260192	54.8394572159012
Trimmed Mean ( 23 / 40 )	265.918918918919	4.72371649270224	56.2944281964724
Trimmed Mean ( 24 / 40 )	266.319444444444	4.61146197309479	57.7516297430759
Trimmed Mean ( 25 / 40 )	266.714285714286	4.49320364883151	59.3594919259105
Trimmed Mean ( 26 / 40 )	267.147058823529	4.35498285175792	61.342849769361
Trimmed Mean ( 27 / 40 )	267.484848484848	4.24869333673035	62.9569675392707
Trimmed Mean ( 28 / 40 )	267.859375	4.13151044597834	64.8332803468371
Trimmed Mean ( 29 / 40 )	268.225806451613	4.00768823240849	66.9278124686905
Trimmed Mean ( 30 / 40 )	268.65	3.88134936347605	69.2156193225036
Trimmed Mean ( 31 / 40 )	269.017241379310	3.78102142766811	71.1493564703818
Trimmed Mean ( 32 / 40 )	269.357142857143	3.68265754650412	73.1420555551897
Trimmed Mean ( 33 / 40 )	269.555555555556	3.61877110485601	74.4881474249201
Trimmed Mean ( 34 / 40 )	269.730769230769	3.54810885669901	76.0209960079167
Trimmed Mean ( 35 / 40 )	269.92	3.46808657472617	77.8296602994439
Trimmed Mean ( 36 / 40 )	270.104166666667	3.37140136268958	80.1162892249612
Trimmed Mean ( 37 / 40 )	270.239130434783	3.27929896812219	82.4075917022987
Trimmed Mean ( 38 / 40 )	270.386363636364	3.17215953230678	85.237315741097
Trimmed Mean ( 39 / 40 )	270.595238095238	3.05867125239188	88.4682320414895
Trimmed Mean ( 40 / 40 )	270.775	2.94075855816759	92.0765831822394
Median	272
Midrange	231
Midmean - Weighted Average at Xnp	267.459016393443
Midmean - Weighted Average at X(n+1)p	268.65
Midmean - Empirical Distribution Function	267.459016393443
Midmean - Empirical Distribution Function - Averaging	268.65
Midmean - Empirical Distribution Function - Interpolation	268.65
Midmean - Closest Observation	267.459016393443
Midmean - True Basic - Statistics Graphics Toolkit	268.65
Midmean - MS Excel (old versions)	268.225806451613
Number of observations	120

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Jul/20/t1279624487ce37l5paf5jcqvk/124hs1279623974.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Jul/20/t1279624487ce37l5paf5jcqvk/124hs1279623974.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Jul/20/t1279624487ce37l5paf5jcqvk/224hs1279623974.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Jul/20/t1279624487ce37l5paf5jcqvk/224hs1279623974.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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