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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_centraltendency.wasp
Title produced by softwareCentral Tendency
Date of computationWed, 30 Jan 2019 15:16:07 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2019/Jan/30/t1548857803y90ie437cdqu6w2.htm/, Retrieved Sun, 28 Apr 2024 08:08:24 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=317048, Retrieved Sun, 28 Apr 2024 08:08:24 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact93

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Central Tendency] [] [2019-01-30 14:16:07] [e8f0be38fc169c976f4045548a5919a7] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
19.6427
13.7242
14.8027
8.42832
6.80835
8.82499
8.76937
7.69536
7.65933
1.86731
3.72965
3.26542
-7.7517
0.957393
-3.04433
-12.5655
-6.9441
-6.8168
-8.56987
-4.46034
-11.229
-3.03305
-9.87928
-4.30931
-2.82241
-2.62636
-4.92814
-2.61029
-6.89788
-7.6867

Tables (Output of Computation)





Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time2 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=317048&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]2 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=317048&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=317048&T=0

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R ServerBig Analytics Cloud Computing Center






Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean1.1e-061.528177.19816e-07
Geometric MeanNaN
Harmonic Mean-71.8167
Quadratic Mean8.22943
Winsorized Mean ( 1 / 10 )-0.1167821.45143-0.0804602
Winsorized Mean ( 2 / 10 )-0.09870091.40377-0.0703115
Winsorized Mean ( 3 / 10 )-0.4576811.22451-0.373766
Winsorized Mean ( 4 / 10 )-0.3560081.19849-0.297046
Winsorized Mean ( 5 / 10 )-0.4020161.1814-0.340288
Winsorized Mean ( 6 / 10 )-0.4000881.11325-0.359387
Winsorized Mean ( 7 / 10 )-0.397711.10896-0.358634
Winsorized Mean ( 8 / 10 )-0.6030171.04846-0.575145
Winsorized Mean ( 9 / 10 )-0.9600290.717591-1.33785
Winsorized Mean ( 10 / 10 )-0.9588390.653611-1.46699
Trimmed Mean ( 1 / 10 )-0.2527561.40209-0.180271
Trimmed Mean ( 2 / 10 )-0.4096491.3234-0.309542
Trimmed Mean ( 3 / 10 )-0.6039911.23949-0.487289
Trimmed Mean ( 4 / 10 )-0.6704961.22704-0.546432
Trimmed Mean ( 5 / 10 )-0.7884291.20969-0.651763
Trimmed Mean ( 6 / 10 )-0.9172331.17606-0.779918
Trimmed Mean ( 7 / 10 )-1.078841.14076-0.945723
Trimmed Mean ( 8 / 10 )-1.287351.05219-1.22349
Trimmed Mean ( 9 / 10 )-1.50120.891158-1.68456
Trimmed Mean ( 10 / 10 )-1.68160.852436-1.9727
Median-2.72438
Midrange3.5386
Midmean - Weighted Average at Xnp-1.66139
Midmean - Weighted Average at X(n+1)p-1.07884
Midmean - Empirical Distribution Function-1.07884
Midmean - Empirical Distribution Function - Averaging-1.07884
Midmean - Empirical Distribution Function - Interpolation-1.28735
Midmean - Closest Observation-1.07884
Midmean - True Basic - Statistics Graphics Toolkit-1.07884
Midmean - MS Excel (old versions)-1.07884
Number of observations30

\begin{tabular}{lllllllll}
\hline
Central Tendency - Ungrouped Data \tabularnewline
Measure & Value & S.E. & Value/S.E. \tabularnewline
Arithmetic Mean & 1.1e-06 & 1.52817 & 7.19816e-07 \tabularnewline
Geometric Mean & NaN &  &  \tabularnewline
Harmonic Mean & -71.8167 &  &  \tabularnewline
Quadratic Mean & 8.22943 &  &  \tabularnewline
Winsorized Mean ( 1 / 10 ) & -0.116782 & 1.45143 & -0.0804602 \tabularnewline
Winsorized Mean ( 2 / 10 ) & -0.0987009 & 1.40377 & -0.0703115 \tabularnewline
Winsorized Mean ( 3 / 10 ) & -0.457681 & 1.22451 & -0.373766 \tabularnewline
Winsorized Mean ( 4 / 10 ) & -0.356008 & 1.19849 & -0.297046 \tabularnewline
Winsorized Mean ( 5 / 10 ) & -0.402016 & 1.1814 & -0.340288 \tabularnewline
Winsorized Mean ( 6 / 10 ) & -0.400088 & 1.11325 & -0.359387 \tabularnewline
Winsorized Mean ( 7 / 10 ) & -0.39771 & 1.10896 & -0.358634 \tabularnewline
Winsorized Mean ( 8 / 10 ) & -0.603017 & 1.04846 & -0.575145 \tabularnewline
Winsorized Mean ( 9 / 10 ) & -0.960029 & 0.717591 & -1.33785 \tabularnewline
Winsorized Mean ( 10 / 10 ) & -0.958839 & 0.653611 & -1.46699 \tabularnewline
Trimmed Mean ( 1 / 10 ) & -0.252756 & 1.40209 & -0.180271 \tabularnewline
Trimmed Mean ( 2 / 10 ) & -0.409649 & 1.3234 & -0.309542 \tabularnewline
Trimmed Mean ( 3 / 10 ) & -0.603991 & 1.23949 & -0.487289 \tabularnewline
Trimmed Mean ( 4 / 10 ) & -0.670496 & 1.22704 & -0.546432 \tabularnewline
Trimmed Mean ( 5 / 10 ) & -0.788429 & 1.20969 & -0.651763 \tabularnewline
Trimmed Mean ( 6 / 10 ) & -0.917233 & 1.17606 & -0.779918 \tabularnewline
Trimmed Mean ( 7 / 10 ) & -1.07884 & 1.14076 & -0.945723 \tabularnewline
Trimmed Mean ( 8 / 10 ) & -1.28735 & 1.05219 & -1.22349 \tabularnewline
Trimmed Mean ( 9 / 10 ) & -1.5012 & 0.891158 & -1.68456 \tabularnewline
Trimmed Mean ( 10 / 10 ) & -1.6816 & 0.852436 & -1.9727 \tabularnewline
Median & -2.72438 &  &  \tabularnewline
Midrange & 3.5386 &  &  \tabularnewline
Midmean - Weighted Average at Xnp & -1.66139 &  &  \tabularnewline
Midmean - Weighted Average at X(n+1)p & -1.07884 &  &  \tabularnewline
Midmean - Empirical Distribution Function & -1.07884 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Averaging & -1.07884 &  &  \tabularnewline
Midmean - Empirical Distribution Function - Interpolation & -1.28735 &  &  \tabularnewline
Midmean - Closest Observation & -1.07884 &  &  \tabularnewline
Midmean - True Basic - Statistics Graphics Toolkit & -1.07884 &  &  \tabularnewline
Midmean - MS Excel (old versions) & -1.07884 &  &  \tabularnewline
Number of observations & 30 &  &  \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=317048&T=1

[TABLE]
[ROW][C]Central Tendency - Ungrouped Data[/C][/ROW]
[ROW][C]Measure[/C][C]Value[/C][C]S.E.[/C][C]Value/S.E.[/C][/ROW]
[ROW][C]Arithmetic Mean[/C][C]1.1e-06[/C][C]1.52817[/C][C]7.19816e-07[/C][/ROW]
[ROW][C]Geometric Mean[/C][C]NaN[/C][C][/C][C][/C][/ROW]
[ROW][C]Harmonic Mean[/C][C]-71.8167[/C][C][/C][C][/C][/ROW]
[ROW][C]Quadratic Mean[/C][C]8.22943[/C][C][/C][C][/C][/ROW]
[ROW][C]Winsorized Mean ( 1 / 10 )[/C][C]-0.116782[/C][C]1.45143[/C][C]-0.0804602[/C][/ROW]
[ROW][C]Winsorized Mean ( 2 / 10 )[/C][C]-0.0987009[/C][C]1.40377[/C][C]-0.0703115[/C][/ROW]
[ROW][C]Winsorized Mean ( 3 / 10 )[/C][C]-0.457681[/C][C]1.22451[/C][C]-0.373766[/C][/ROW]
[ROW][C]Winsorized Mean ( 4 / 10 )[/C][C]-0.356008[/C][C]1.19849[/C][C]-0.297046[/C][/ROW]
[ROW][C]Winsorized Mean ( 5 / 10 )[/C][C]-0.402016[/C][C]1.1814[/C][C]-0.340288[/C][/ROW]
[ROW][C]Winsorized Mean ( 6 / 10 )[/C][C]-0.400088[/C][C]1.11325[/C][C]-0.359387[/C][/ROW]
[ROW][C]Winsorized Mean ( 7 / 10 )[/C][C]-0.39771[/C][C]1.10896[/C][C]-0.358634[/C][/ROW]
[ROW][C]Winsorized Mean ( 8 / 10 )[/C][C]-0.603017[/C][C]1.04846[/C][C]-0.575145[/C][/ROW]
[ROW][C]Winsorized Mean ( 9 / 10 )[/C][C]-0.960029[/C][C]0.717591[/C][C]-1.33785[/C][/ROW]
[ROW][C]Winsorized Mean ( 10 / 10 )[/C][C]-0.958839[/C][C]0.653611[/C][C]-1.46699[/C][/ROW]
[ROW][C]Trimmed Mean ( 1 / 10 )[/C][C]-0.252756[/C][C]1.40209[/C][C]-0.180271[/C][/ROW]
[ROW][C]Trimmed Mean ( 2 / 10 )[/C][C]-0.409649[/C][C]1.3234[/C][C]-0.309542[/C][/ROW]
[ROW][C]Trimmed Mean ( 3 / 10 )[/C][C]-0.603991[/C][C]1.23949[/C][C]-0.487289[/C][/ROW]
[ROW][C]Trimmed Mean ( 4 / 10 )[/C][C]-0.670496[/C][C]1.22704[/C][C]-0.546432[/C][/ROW]
[ROW][C]Trimmed Mean ( 5 / 10 )[/C][C]-0.788429[/C][C]1.20969[/C][C]-0.651763[/C][/ROW]
[ROW][C]Trimmed Mean ( 6 / 10 )[/C][C]-0.917233[/C][C]1.17606[/C][C]-0.779918[/C][/ROW]
[ROW][C]Trimmed Mean ( 7 / 10 )[/C][C]-1.07884[/C][C]1.14076[/C][C]-0.945723[/C][/ROW]
[ROW][C]Trimmed Mean ( 8 / 10 )[/C][C]-1.28735[/C][C]1.05219[/C][C]-1.22349[/C][/ROW]
[ROW][C]Trimmed Mean ( 9 / 10 )[/C][C]-1.5012[/C][C]0.891158[/C][C]-1.68456[/C][/ROW]
[ROW][C]Trimmed Mean ( 10 / 10 )[/C][C]-1.6816[/C][C]0.852436[/C][C]-1.9727[/C][/ROW]
[ROW][C]Median[/C][C]-2.72438[/C][C][/C][C][/C][/ROW]
[ROW][C]Midrange[/C][C]3.5386[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at Xnp[/C][C]-1.66139[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Weighted Average at X(n+1)p[/C][C]-1.07884[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function[/C][C]-1.07884[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Averaging[/C][C]-1.07884[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Empirical Distribution Function - Interpolation[/C][C]-1.28735[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - Closest Observation[/C][C]-1.07884[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - True Basic - Statistics Graphics Toolkit[/C][C]-1.07884[/C][C][/C][C][/C][/ROW]
[ROW][C]Midmean - MS Excel (old versions)[/C][C]-1.07884[/C][C][/C][C][/C][/ROW]
[ROW][C]Number of observations[/C][C]30[/C][C][/C][C][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=317048&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=317048&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Central Tendency - Ungrouped Data
MeasureValueS.E.Value/S.E.
Arithmetic Mean1.1e-061.528177.19816e-07
Geometric MeanNaN
Harmonic Mean-71.8167
Quadratic Mean8.22943
Winsorized Mean ( 1 / 10 )-0.1167821.45143-0.0804602
Winsorized Mean ( 2 / 10 )-0.09870091.40377-0.0703115
Winsorized Mean ( 3 / 10 )-0.4576811.22451-0.373766
Winsorized Mean ( 4 / 10 )-0.3560081.19849-0.297046
Winsorized Mean ( 5 / 10 )-0.4020161.1814-0.340288
Winsorized Mean ( 6 / 10 )-0.4000881.11325-0.359387
Winsorized Mean ( 7 / 10 )-0.397711.10896-0.358634
Winsorized Mean ( 8 / 10 )-0.6030171.04846-0.575145
Winsorized Mean ( 9 / 10 )-0.9600290.717591-1.33785
Winsorized Mean ( 10 / 10 )-0.9588390.653611-1.46699
Trimmed Mean ( 1 / 10 )-0.2527561.40209-0.180271
Trimmed Mean ( 2 / 10 )-0.4096491.3234-0.309542
Trimmed Mean ( 3 / 10 )-0.6039911.23949-0.487289
Trimmed Mean ( 4 / 10 )-0.6704961.22704-0.546432
Trimmed Mean ( 5 / 10 )-0.7884291.20969-0.651763
Trimmed Mean ( 6 / 10 )-0.9172331.17606-0.779918
Trimmed Mean ( 7 / 10 )-1.078841.14076-0.945723
Trimmed Mean ( 8 / 10 )-1.287351.05219-1.22349
Trimmed Mean ( 9 / 10 )-1.50120.891158-1.68456
Trimmed Mean ( 10 / 10 )-1.68160.852436-1.9727
Median-2.72438
Midrange3.5386
Midmean - Weighted Average at Xnp-1.66139
Midmean - Weighted Average at X(n+1)p-1.07884
Midmean - Empirical Distribution Function-1.07884
Midmean - Empirical Distribution Function - Averaging-1.07884
Midmean - Empirical Distribution Function - Interpolation-1.28735
Midmean - Closest Observation-1.07884
Midmean - True Basic - Statistics Graphics Toolkit-1.07884
Midmean - MS Excel (old versions)-1.07884
Number of observations30


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ; par6 = 12 ;
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,'Arithmetic Mean',header=TRUE)
a<-table.element(a,signif(arm,6))
a<-table.element(a, signif(armse,6))
a<-table.element(a,signif(armose,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Geometric Mean',header=TRUE)
a<-table.element(a,signif(geo,6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Harmonic Mean',header=TRUE)
a<-table.element(a,signif(har,6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Quadratic Mean',header=TRUE)
a<-table.element(a,signif(qua,6))
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, mylabel,header=TRUE)
a<-table.element(a,signif(win[j,1],6))
a<-table.element(a,signif(win[j,2],6))
a<-table.element(a,signif(win[j,1]/win[j,2],6))
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, mylabel,header=TRUE)
a<-table.element(a,signif(tri[j,1],6))
a<-table.element(a,signif(tri[j,2],6))
a<-table.element(a,signif(tri[j,1]/tri[j,2],6))
a<-table.row.end(a)
}
a<-table.row.start(a)
a<-table.element(a, 'Median',header=TRUE)
a<-table.element(a,signif(median(x),6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Midrange',header=TRUE)
a<-table.element(a,signif(midr,6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <-  'Midmean'
mylabel <- paste(mymid,'Weighted Average at Xnp',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[1],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <-  'Midmean'
mylabel <- paste(mymid,'Weighted Average at X(n+1)p',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[2],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <-  'Midmean'
mylabel <- paste(mymid,'Empirical Distribution Function',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[3],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <-  'Midmean'
mylabel <- paste(mymid,'Empirical Distribution Function - Averaging',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[4],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <-  'Midmean'
mylabel <- paste(mymid,'Empirical Distribution Function - Interpolation',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[5],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <-  'Midmean'
mylabel <- paste(mymid,'Closest Observation',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[6],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <-  'Midmean'
mylabel <- paste(mymid,'True Basic - Statistics Graphics Toolkit',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[7],6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
mymid <-  'Midmean'
mylabel <- paste(mymid,'MS Excel (old versions)',sep=' - ')
a<-table.element(a,mylabel,header=TRUE)
a<-table.element(a,signif(midm[8],6))
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,signif(length(x),6))
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')