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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: Mon, 02 Aug 2010 10:42:47 +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/02/t12807457748p2uwfil5ulzpgf.htm/, Retrieved Mon, 02 Aug 2010 12:42:55 +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/02/t12807457748p2uwfil5ulzpgf.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:

Bogaerts Yannik

Dataseries X:

» Textbox « » Textfile « » CSV «

442 441 440 438 458 457 442 432 433 433 434 436 439 439 441 436 460 453 435 421 412 408 402 409 410 410 416 410 437 431 411 398 394 395 389 404 397 401 402 383 406 400 377 372 362 365 361 372 355 365 367 341 370 366 333 320 298 306 293 313 293 304 304 286 320 313 283 272 251 262 247 268 251 257 261 242 274 272 243 234 217 231 209 226 208 214 222 194 230 226 197 188 175 190 165 176 159 169 170 141 170 164 132 123 113 125 101 99 87 90 89 66 102 97 65 54 33 49 30 34

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	292.816666666667	11.3993769998654	25.6870762911099
Geometric Mean	253.873187730441
Harmonic Mean	196.232360699272
Quadratic Mean	318.127568751908
Winsorized Mean ( 1 / 40 )	292.825	11.392517216551	25.7032747402465
Winsorized Mean ( 2 / 40 )	292.825	11.3873035009351	25.7150430719576
Winsorized Mean ( 3 / 40 )	293.1	11.3054633430285	25.9255185839633
Winsorized Mean ( 4 / 40 )	292.9	11.2332065756839	26.0744782023353
Winsorized Mean ( 5 / 40 )	293.358333333333	11.1528142422832	26.3035254564839
Winsorized Mean ( 6 / 40 )	293.358333333333	11.1386399141152	26.3369976581773
Winsorized Mean ( 7 / 40 )	294.583333333333	10.9358108272796	26.937493523433
Winsorized Mean ( 8 / 40 )	294.65	10.9071305666926	27.0144377752093
Winsorized Mean ( 9 / 40 )	294.65	10.8868875592748	27.064668243862
Winsorized Mean ( 10 / 40 )	295.233333333333	10.7958048531658	27.3470424251656
Winsorized Mean ( 11 / 40 )	295.325	10.7573645056046	27.453285592966
Winsorized Mean ( 12 / 40 )	295.425	10.715656903389	27.569471723807
Winsorized Mean ( 13 / 40 )	295.425	10.6871585977545	27.6429882927042
Winsorized Mean ( 14 / 40 )	296.708333333333	10.4951529150628	28.2709871627972
Winsorized Mean ( 15 / 40 )	297.833333333333	10.3000797727006	28.9156336558395
Winsorized Mean ( 16 / 40 )	297.966666666667	10.2472510034603	29.0777171912789
Winsorized Mean ( 17 / 40 )	298.816666666667	10.0922217000125	29.6086110223179
Winsorized Mean ( 18 / 40 )	300.166666666667	9.9073108657245	30.2974914923815
Winsorized Mean ( 19 / 40 )	302.858333333333	9.51571967772594	31.8271600667528
Winsorized Mean ( 20 / 40 )	303.525	9.39175365758205	32.3182454594048
Winsorized Mean ( 21 / 40 )	301.95	9.17458926793424	32.9115550769487
Winsorized Mean ( 22 / 40 )	301.766666666667	8.98409529412774	33.5889877374642
Winsorized Mean ( 23 / 40 )	301.191666666667	8.8791315457915	33.9212979460164
Winsorized Mean ( 24 / 40 )	300.991666666667	8.85820842830481	33.9788422346106
Winsorized Mean ( 25 / 40 )	301.825	8.70798968670459	34.660697917549
Winsorized Mean ( 26 / 40 )	302.041666666667	8.68151385933482	34.7913591524012
Winsorized Mean ( 27 / 40 )	304.741666666667	8.35823865883584	36.4600341178954
Winsorized Mean ( 28 / 40 )	304.975	8.27895531999516	36.8373772066906
Winsorized Mean ( 29 / 40 )	305.7	8.14129942346558	37.5492883996975
Winsorized Mean ( 30 / 40 )	305.95	8.00249304641892	38.2318357823393
Winsorized Mean ( 31 / 40 )	308.275	7.62847902447734	40.4110700194422
Winsorized Mean ( 32 / 40 )	308.008333333333	7.54299994404939	40.8336650693361
Winsorized Mean ( 33 / 40 )	309.383333333333	7.3926129316399	41.8503357600657
Winsorized Mean ( 34 / 40 )	309.95	7.27105124961376	42.6279487462648
Winsorized Mean ( 35 / 40 )	311.116666666667	7.08491101230549	43.9125722435047
Winsorized Mean ( 36 / 40 )	311.716666666667	6.89563235424371	45.2049428758814
Winsorized Mean ( 37 / 40 )	311.408333333333	6.86326534392625	45.3732032390266
Winsorized Mean ( 38 / 40 )	312.041666666667	6.66520707936603	46.8164999153105
Winsorized Mean ( 39 / 40 )	312.041666666667	6.59766527580047	47.2957710981796
Winsorized Mean ( 40 / 40 )	311.375	6.32162114552612	49.2555616402864
Trimmed Mean ( 1 / 40 )	293.627118644068	11.2860095165815	26.016912196704
Trimmed Mean ( 2 / 40 )	294.456896551724	11.1669247661046	26.3686648490281
Trimmed Mean ( 3 / 40 )	295.315789473684	11.0367645476282	26.7574603226585
Trimmed Mean ( 4 / 40 )	296.107142857143	10.9239823685663	27.106153494827
Trimmed Mean ( 5 / 40 )	296.981818181818	10.8194985216466	27.448759994527
Trimmed Mean ( 6 / 40 )	297.787037037037	10.7226436430287	27.771792754732
Trimmed Mean ( 7 / 40 )	298.622641509434	10.6159913689568	28.1295105780382
Trimmed Mean ( 8 / 40 )	299.288461538462	10.5365811885812	28.404703212728
Trimmed Mean ( 9 / 40 )	299.970588235294	10.450783749133	28.7031667132315
Trimmed Mean ( 10 / 40 )	300.68	10.3558199125229	29.0348811141838
Trimmed Mean ( 11 / 40 )	301.34693877551	10.2618986890618	29.3656123400162
Trimmed Mean ( 12 / 40 )	302.03125	10.1598026849732	29.728062578097
Trimmed Mean ( 13 / 40 )	302.734042553192	10.0485230390823	30.1272178384576
Trimmed Mean ( 14 / 40 )	303.467391304348	9.9244693076482	30.577694574609
Trimmed Mean ( 15 / 40 )	304.111111111111	9.80917103101564	31.0027330698528
Trimmed Mean ( 16 / 40 )	304.681818181818	9.7027334783863	31.4016476759384
Trimmed Mean ( 17 / 40 )	305.267441860465	9.5859624970847	31.8452572658514
Trimmed Mean ( 18 / 40 )	305.809523809524	9.4707854110675	32.2897743467144
Trimmed Mean ( 19 / 40 )	306.268292682927	9.36079726188134	32.7181845856336
Trimmed Mean ( 20 / 40 )	306.5375	9.28197422375791	33.0250324564999
Trimmed Mean ( 21 / 40 )	306.769230769231	9.20307617491165	33.333336043171
Trimmed Mean ( 22 / 40 )	307.131578947368	9.13380730179962	33.6258001509244
Trimmed Mean ( 23 / 40 )	307.527027027027	9.07195357766345	33.8986552779774
Trimmed Mean ( 24 / 40 )	307.986111111111	9.00728910738347	34.1929860848641
Trimmed Mean ( 25 / 40 )	308.485714285714	8.92890583224707	34.549106025019
Trimmed Mean ( 26 / 40 )	308.955882352941	8.85120969157229	34.9054980187753
Trimmed Mean ( 27 / 40 )	309.439393939394	8.75771065623917	35.333365771675
Trimmed Mean ( 28 / 40 )	309.765625	8.68549757633732	35.664695347325
Trimmed Mean ( 29 / 40 )	310.096774193548	8.60385306173285	36.0416166999363
Trimmed Mean ( 30 / 40 )	310.4	8.51881268085673	36.4370026233261
Trimmed Mean ( 31 / 40 )	310.706896551724	8.42916495935943	36.8609343926443
Trimmed Mean ( 32 / 40 )	310.875	8.36737877697685	37.1532122885824
Trimmed Mean ( 33 / 40 )	311.074074074074	8.29563177432476	37.498539295929
Trimmed Mean ( 34 / 40 )	311.192307692308	8.22166684912083	37.8502697084575
Trimmed Mean ( 35 / 40 )	311.28	8.13975078593582	38.2419570557174
Trimmed Mean ( 36 / 40 )	311.291666666667	8.05796588012729	38.6315443993602
Trimmed Mean ( 37 / 40 )	311.260869565217	7.97613801082566	39.0240075012189
Trimmed Mean ( 38 / 40 )	311.25	7.86615875051935	39.5682327132605
Trimmed Mean ( 39 / 40 )	311.190476190476	7.75100593638195	40.1483986394333
Trimmed Mean ( 40 / 40 )	311.125	7.60256261620602	40.9237010868927
Median	305
Midrange	245
Midmean - Weighted Average at Xnp	308.491803278689
Midmean - Weighted Average at X(n+1)p	310.4
Midmean - Empirical Distribution Function	308.491803278689
Midmean - Empirical Distribution Function - Averaging	310.4
Midmean - Empirical Distribution Function - Interpolation	310.4
Midmean - Closest Observation	308.491803278689
Midmean - True Basic - Statistics Graphics Toolkit	310.4
Midmean - MS Excel (old versions)	310.096774193548
Number of observations	120

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Aug/02/t12807457748p2uwfil5ulzpgf/1ic5r1280745763.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Aug/02/t12807457748p2uwfil5ulzpgf/1ic5r1280745763.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/Aug/02/t12807457748p2uwfil5ulzpgf/2bl4c1280745763.png (open in new window)

http://www.freestatistics.org/blog/date/2010/Aug/02/t12807457748p2uwfil5ulzpgf/2bl4c1280745763.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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