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ct dow jones

*Unverified author*
R Software Module: /rwasp_centraltendency.wasp (opens new window with default values)
Title produced by software: Central Tendency
Date of computation: Mon, 28 Dec 2009 06:23:43 -0700
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Dec/28/t1262006747zhsode51bk3mtd8.htm/, Retrieved Mon, 28 Dec 2009 14:25:49 +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/Dec/28/t1262006747zhsode51bk3mtd8.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 «
10967,87 10433,56 10665,78 10666,71 10682,74 10777,22 10052,6 10213,97 10546,82 10767,2 10444,5 10314,68 9042,56 9220,75 9721,84 9978,53 9923,81 9892,56 10500,98 10179,35 10080,48 9492,44 8616,49 8685,4 8160,67 8048,1 8641,21 8526,63 8474,21 7916,13 7977,64 8334,59 8623,36 9098,03 9154,34 9284,73 9492,49 9682,35 9762,12 10124,63 10540,05 10601,61 10323,73 10418,4 10092,96 10364,91 10152,09 10032,8 10204,59 10001,6 10411,75 10673,38 10539,51 10723,78 10682,06 10283,19 10377,18 10486,64 10545,38 10554,27 10532,54 10324,31 10695,25 10827,81 10872,48 10971,19 11145,65 11234,68 11333,88 10997,97 11036,89 11257,35 11533,59 11963,12 12185,15 12377,62 12512,89 12631,48 12268,53 12754,8 13407,75 13480,21 13673,28 13239,71 13557,69 13901,28 13200,58 13406,97 12538,12 12419,57 12193,88 12656,63 12812,48 12056,67 11322,38 11530,75 11114,08 9181,73 8614,55 8595,56 8396,20 7690,50 7235,47 7992,12 8398,37 8593 8679,75 etc...
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135


Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean10447.1367567568141.76888681968573.6913224835036
Geometric Mean10341.9271919112
Harmonic Mean10237.1865467561
Quadratic Mean10552.4164206161
Winsorized Mean ( 1 / 37 )10449.1820720721140.53901969479974.350753938401
Winsorized Mean ( 2 / 37 )10451.1647747748139.41200728287874.9660303905426
Winsorized Mean ( 3 / 37 )10450.7331531532138.71989635437975.3369446474736
Winsorized Mean ( 4 / 37 )10448.6437837838138.12193435355275.6479688232452
Winsorized Mean ( 5 / 37 )10451.1302702703137.71121904032975.8916400791547
Winsorized Mean ( 6 / 37 )10448.1740540541135.02787680052577.3779037456765
Winsorized Mean ( 7 / 37 )10456.6743243243132.92357353095678.6668161753047
Winsorized Mean ( 8 / 37 )10433.1435135135127.27149713786181.9754913561857
Winsorized Mean ( 9 / 37 )10428.6427027027126.45738334088882.4676458359929
Winsorized Mean ( 10 / 37 )10426.630990991124.00714383670984.0808897648725
Winsorized Mean ( 11 / 37 )10429.3334234234122.86289336666784.8859500019954
Winsorized Mean ( 12 / 37 )10426.4155855856120.23217017977186.719016798882
Winsorized Mean ( 13 / 37 )10423.7605405405119.72029905237487.067611950923
Winsorized Mean ( 14 / 37 )10414.3855855856117.54087956656788.6022431003467
Winsorized Mean ( 15 / 37 )10408.9788288288116.62976986417689.2480439681125
Winsorized Mean ( 16 / 37 )10394.2444144144114.10990873801491.0897618740423
Winsorized Mean ( 17 / 37 )10385.5453153153112.03104370891992.7023882978294
Winsorized Mean ( 18 / 37 )10390.3793693694110.94272064035693.6553503411186
Winsorized Mean ( 19 / 37 )10369.3544144144107.62098257007296.3506759256996
Winsorized Mean ( 20 / 37 )10416.851711711796.424145543521108.031568783880
Winsorized Mean ( 21 / 37 )10346.083603603683.8323445926352123.413983634576
Winsorized Mean ( 22 / 37 )10356.681261261382.2627607420244125.897564922964
Winsorized Mean ( 23 / 37 )10321.563783783876.3905075149762135.115790162282
Winsorized Mean ( 24 / 37 )10327.514054054174.9521804773062137.788040164902
Winsorized Mean ( 25 / 37 )10327.277567567671.273891181008144.895660899730
Winsorized Mean ( 26 / 37 )10343.025135135167.8753639185379152.382610390841
Winsorized Mean ( 27 / 37 )10350.025675675761.6376015426055167.917398092161
Winsorized Mean ( 28 / 37 )10342.074684684760.7083803340334170.356623381811
Winsorized Mean ( 29 / 37 )10359.132432432453.7322356811009192.791762730915
Winsorized Mean ( 30 / 37 )10361.418918918950.9717206979992203.277793588899
Winsorized Mean ( 31 / 37 )10364.968558558648.796032328173212.414166972633
Winsorized Mean ( 32 / 37 )10375.623693693747.3071587999668219.324600269610
Winsorized Mean ( 33 / 37 )10375.573153153240.8156564237739254.205715704469
Winsorized Mean ( 34 / 37 )10372.678558558638.0733951452254272.439022550879
Winsorized Mean ( 35 / 37 )10366.580360360435.2329630910096294.229592145930
Winsorized Mean ( 36 / 37 )10381.077657657732.8852886266524315.675430905118
Winsorized Mean ( 37 / 37 )10374.294324324330.5034024924071340.102856620887
Trimmed Mean ( 1 / 37 )10444.9122018349137.68239271736775.8623669714696
Trimmed Mean ( 2 / 37 )10440.4827102804134.48832018797277.6311481598396
Trimmed Mean ( 3 / 37 )10434.8364761905131.57655492312979.3061992106938
Trimmed Mean ( 4 / 37 )10429.1260194175128.59556482684181.1001999443816
Trimmed Mean ( 5 / 37 )10423.7634653465125.43852578319883.0985807610849
Trimmed Mean ( 6 / 37 )10417.6266666667121.98737958284585.3992167246428
Trimmed Mean ( 7 / 37 )10417.6266666667118.74983866536587.7275016433781
Trimmed Mean ( 8 / 37 )10404.3104210526115.54242736195490.0475319638177
Trimmed Mean ( 9 / 37 )10400.0087096774113.06767320715291.9803902802837
Trimmed Mean ( 10 / 37 )10396.1279120879110.40467787725394.1638353734095
Trimmed Mean ( 11 / 37 )10392.3235955056107.80600767413096.3983716651394
Trimmed Mean ( 12 / 37 )10388.0309195402105.02499444454398.9100830186238
Trimmed Mean ( 13 / 37 )10383.8537647059102.27237775468101.531361572658
Trimmed Mean ( 14 / 37 )10383.853764705999.180920829916104.696081442045
Trimmed Mean ( 15 / 37 )10376.358024691495.9615944415258108.130321146489
Trimmed Mean ( 16 / 37 )10373.302405063392.3642580873633112.308620454155
Trimmed Mean ( 17 / 37 )10371.415584415688.5773911834262117.088745173567
Trimmed Mean ( 18 / 37 )10370.185466666784.4691134421586122.768963045502
Trimmed Mean ( 19 / 37 )10368.479589041179.772724622041129.975247030441
Trimmed Mean ( 20 / 37 )10368.407605633874.7427484251917138.721251547383
Trimmed Mean ( 21 / 37 )10364.511014492870.714853583333146.567665621747
Trimmed Mean ( 22 / 37 )10365.964776119468.0740897780619152.274746675497
Trimmed Mean ( 23 / 37 )10366.685384615465.1682664940555159.075665846674
Trimmed Mean ( 24 / 37 )10370.141904761962.6410930156593165.548546577397
Trimmed Mean ( 25 / 37 )10373.373934426259.8227860504248173.401718965119
Trimmed Mean ( 26 / 37 )10376.842881355957.033148595302181.944064757644
Trimmed Mean ( 27 / 37 )10379.375789473754.238671305367191.364860894862
Trimmed Mean ( 28 / 37 )10379.375789473751.9525698181006199.785608793069
Trimmed Mean ( 29 / 37 )10384.523773584949.2643261823036210.791957960752
Trimmed Mean ( 30 / 37 )10386.429411764747.2836336560397219.662251156918
Trimmed Mean ( 31 / 37 )10386.429411764745.3222478105059229.168452879716
Trimmed Mean ( 32 / 37 )10390.096808510643.2661462560595240.143800814141
Trimmed Mean ( 33 / 37 )10391.212444444440.9418379443099253.80424930065
Trimmed Mean ( 34 / 37 )10392.435813953539.3907147406301263.829582234873
Trimmed Mean ( 35 / 37 )10394.009024390237.9562723259100273.841670624093
Trimmed Mean ( 36 / 37 )10396.239487179536.6861172853923283.383477360224
Trimmed Mean ( 37 / 37 )10397.502972973035.5399062613676292.558536775749
Median10418.4
Midrange10568.375
Midmean - Weighted Average at Xnp10365.6923214286
Midmean - Weighted Average at X(n+1)p10379.3757894737
Midmean - Empirical Distribution Function10379.3757894737
Midmean - Empirical Distribution Function - Averaging10379.3757894737
Midmean - Empirical Distribution Function - Interpolation10381.5696363636
Midmean - Closest Observation10365.6923214286
Midmean - True Basic - Statistics Graphics Toolkit10379.3757894737
Midmean - MS Excel (old versions)10379.3757894737
Number of observations111
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2009/Dec/28/t1262006747zhsode51bk3mtd8/1qdgd1262006621.png (open in new window)
http://www.freestatistics.org/blog/date/2009/Dec/28/t1262006747zhsode51bk3mtd8/1qdgd1262006621.ps (open in new window)


http://www.freestatistics.org/blog/date/2009/Dec/28/t1262006747zhsode51bk3mtd8/2jvxg1262006621.png (open in new window)
http://www.freestatistics.org/blog/date/2009/Dec/28/t1262006747zhsode51bk3mtd8/2jvxg1262006621.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')
 




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