Home » date » 2009 » Apr » 23 »

centrummaten-ruwe aardolie-Katrijn kempenaers

*Unverified author*

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

Title produced by software: Central Tendency

Date of computation: Thu, 23 Apr 2009 04:40:02 -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/Apr/23/t124048338881ucynjnt75h35z.htm/, Retrieved Thu, 23 Apr 2009 12:43:11 +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/2009/Apr/23/t124048338881ucynjnt75h35z.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 «

66 66,3 68,4 70,6 75 83,3 83,9 87 87,1 88,5 88,6 89,5 90 90,1 90,5 90,6 90,6 90,8 90,8 91 91,3 92,1 94,1 94,7 95 95,1 96,3 96,3 96,4 96,8 96,9 97,2 97,6 99,3 99,8 100,7 101,8 102,5 103,4 103,8 104,6 105,3 106,1 107,1 109,8 110,3 111,5 113,4 114,2 115,2 117,3 118,8 125,9 131,3 133,1 137,7 145,8 146,5 147 149,8 151,7 152,9 156,8 164,4 170,4 180 180,4 188 188,5 191,6 194 199,3 199,5 202,9 203,7 205 205,6 211,1 214 215,2 215,6 217,5 218,2 218,2 219,3 230 230,3 240,2 240,7 241 242,2 247,8 252 253 255,4 259,6 270,3 289,7 315 320,2 322,7 329,5 351,6 360,6 382,2 403 435,4 464 468,8

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	1 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Central Tendency - Ungrouped Data
Measure	Value	S.E.	Value/S.E.
Arithmetic Mean	168.343119266055	8.86232460641377	18.9953682292593
Geometric Mean	147.896339396665
Harmonic Mean	132.222728917344
Quadratic Mean	191.890103774545
Winsorized Mean ( 1 / 36 )	168.301834862385	8.84830544867396	19.0207984838055
Winsorized Mean ( 2 / 36 )	167.815596330275	8.68813356964989	19.3154945173153
Winsorized Mean ( 3 / 36 )	166.984403669725	8.43894093162293	19.7873649102093
Winsorized Mean ( 4 / 36 )	166.382568807339	8.23052947466284	20.2152934777207
Winsorized Mean ( 5 / 36 )	165.772477064220	7.95998347063627	20.8257313191342
Winsorized Mean ( 6 / 36 )	165.310091743119	7.84620766753401	21.0687887381745
Winsorized Mean ( 7 / 36 )	164.089908256881	7.52655226735465	21.8014706373059
Winsorized Mean ( 8 / 36 )	163.598165137615	7.42555978544167	22.0317618960338
Winsorized Mean ( 9 / 36 )	163.507339449541	7.37381811010649	22.1740402337074
Winsorized Mean ( 10 / 36 )	163.039449541284	7.27991047550334	22.395804191536
Winsorized Mean ( 11 / 36 )	160.577064220184	6.79924038263707	23.6169123583632
Winsorized Mean ( 12 / 36 )	158.496330275229	6.43381922164182	24.6348746856433
Winsorized Mean ( 13 / 36 )	157.232110091743	6.23284555494089	25.2263767336738
Winsorized Mean ( 14 / 36 )	156.744036697248	6.14661055572962	25.5008895188808
Winsorized Mean ( 15 / 36 )	156.427522935780	6.09647141911759	25.6586986441448
Winsorized Mean ( 16 / 36 )	156.280733944954	6.0749986858771	25.7252292594349
Winsorized Mean ( 17 / 36 )	155.656880733945	5.97733022915071	26.0412048132836
Winsorized Mean ( 18 / 36 )	154.732110091743	5.84726629057908	26.4622992014306
Winsorized Mean ( 19 / 36 )	154.557798165138	5.81485515073417	26.5798191285338
Winsorized Mean ( 20 / 36 )	154.557798165138	5.80171880011781	26.6400016081440
Winsorized Mean ( 21 / 36 )	154.615596330275	5.77297816422874	26.7826400744635
Winsorized Mean ( 22 / 36 )	153.021100917431	5.46444552745461	28.0030426048935
Winsorized Mean ( 23 / 36 )	153.084403669725	5.44355323183505	28.1221469047928
Winsorized Mean ( 24 / 36 )	150.794495412844	5.1371346706738	29.353813960471
Winsorized Mean ( 25 / 36 )	150.565137614679	5.10377249428029	29.5007541545817
Winsorized Mean ( 26 / 36 )	150.851376146789	5.07512666446314	29.7236672343717
Winsorized Mean ( 27 / 36 )	150.677981651376	5.05385981986323	29.8144362966233
Winsorized Mean ( 28 / 36 )	150.215596330275	4.99182310900539	30.0923316091233
Winsorized Mean ( 29 / 36 )	150.215596330275	4.9683165671315	30.2347071287777
Winsorized Mean ( 30 / 36 )	149.912844036697	4.92568095040757	30.4349480906377
Winsorized Mean ( 31 / 36 )	149.173394495413	4.81840794428722	30.9590628730959
Winsorized Mean ( 32 / 36 )	147.676146788991	4.61673500412785	31.9871395384298
Winsorized Mean ( 33 / 36 )	148.009174311927	4.54424851868070	32.5706601880341
Winsorized Mean ( 34 / 36 )	147.759633027523	4.48180489604066	32.9687785289488
Winsorized Mean ( 35 / 36 )	147.791743119266	4.42358460932479	33.4099505653684
Winsorized Mean ( 36 / 36 )	147.032110091743	4.25899078605343	34.5227584368619
Trimmed Mean ( 1 / 36 )	166.491588785047	8.52075894271087	19.5395257516906
Trimmed Mean ( 2 / 36 )	164.612380952381	8.14557675596082	20.2088060654416
Trimmed Mean ( 3 / 36 )	162.917475728155	7.81513483141824	20.8464062671316
Trimmed Mean ( 4 / 36 )	161.454455445545	7.54714312544459	21.3927909888463
Trimmed Mean ( 5 / 36 )	160.09797979798	7.31329484909363	21.8913612949465
Trimmed Mean ( 6 / 36 )	158.822680412371	7.12438390432644	22.2928301654158
Trimmed Mean ( 7 / 36 )	157.582105263158	6.93696655549408	22.7162844166162
Trimmed Mean ( 8 / 36 )	156.492473118280	6.79525093985317	23.0296827156851
Trimmed Mean ( 9 / 36 )	155.428571428571	6.65322606403325	23.3613843769423
Trimmed Mean ( 10 / 36 )	154.329213483146	6.49897006106074	23.7467186389772
Trimmed Mean ( 11 / 36 )	153.237931034483	6.3380457520045	24.1774731566144
Trimmed Mean ( 12 / 36 )	152.382352941176	6.2377214238488	24.4291693371509
Trimmed Mean ( 13 / 36 )	151.713253012048	6.18048381340386	24.5471483450894
Trimmed Mean ( 14 / 36 )	151.141975308642	6.14279661051386	24.6047500661101
Trimmed Mean ( 15 / 36 )	150.589873417722	6.10872936643689	24.6515869969794
Trimmed Mean ( 16 / 36 )	150.038961038961	6.0730732399446	24.7056070478626
Trimmed Mean ( 17 / 36 )	149.472	6.03117413755211	24.7832340090029
Trimmed Mean ( 18 / 36 )	148.928767123288	5.99259515146493	24.8521322330412
Trimmed Mean ( 19 / 36 )	148.433802816901	5.96187381710772	24.8971728302883
Trimmed Mean ( 20 / 36 )	147.924637681159	5.92594876263819	24.9621864120378
Trimmed Mean ( 21 / 36 )	147.385074626866	5.8809081184195	25.0616183179675
Trimmed Mean ( 22 / 36 )	146.807692307692	5.82687956952531	25.1949075926503
Trimmed Mean ( 23 / 36 )	146.319047619048	5.8017776541767	25.2196923668235
Trimmed Mean ( 24 / 36 )	145.793442622951	5.76863853436644	25.2734578106068
Trimmed Mean ( 25 / 36 )	145.408474576271	5.76681557051095	25.2146913315259
Trimmed Mean ( 26 / 36 )	145.014035087719	5.7616659681075	25.1687681810112
Trimmed Mean ( 27 / 36 )	144.569090909091	5.75083180792239	25.1388139555623
Trimmed Mean ( 28 / 36 )	144.103773584906	5.73241424015962	25.1384089752894
Trimmed Mean ( 29 / 36 )	143.637254901961	5.71085238703853	25.1516315196595
Trimmed Mean ( 30 / 36 )	143.132653061224	5.67837854401008	25.2066064197517
Trimmed Mean ( 31 / 36 )	142.608510638298	5.63560836837143	25.3049007874032
Trimmed Mean ( 32 / 36 )	142.095555555556	5.59131898892513	25.4136020207411
Trimmed Mean ( 33 / 36 )	141.653488372093	5.56245954987939	25.4659808492746
Trimmed Mean ( 34 / 36 )	141.141463414634	5.52499969717443	25.5459676290690
Trimmed Mean ( 35 / 36 )	140.597435897436	5.47524115303917	25.6787659150673
Trimmed Mean ( 36 / 36 )	139.991891891892	5.40692523678586	25.8912201965474
Median	133.1
Midrange	267.4
Midmean - Weighted Average at Xnp	142.365454545455
Midmean - Weighted Average at X(n+1)p	143.707142857143
Midmean - Empirical Distribution Function	143.707142857143
Midmean - Empirical Distribution Function - Averaging	143.707142857143
Midmean - Empirical Distribution Function - Interpolation	143.707142857143
Midmean - Closest Observation	143.707142857143
Midmean - True Basic - Statistics Graphics Toolkit	143.707142857143
Midmean - MS Excel (old versions)	143.707142857143
Number of observations	109

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Apr/23/t124048338881ucynjnt75h35z/11gw91240483200.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Apr/23/t124048338881ucynjnt75h35z/11gw91240483200.ps (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Apr/23/t124048338881ucynjnt75h35z/2xmbd1240483200.png (open in new window)

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Apr/23/t124048338881ucynjnt75h35z/2xmbd1240483200.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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