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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_variancereduction.wasp
Title produced by softwareVariance Reduction Matrix
Date of computationThu, 22 Nov 2007 07:07:14 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2007/Nov/22/t1195739951qcjdvd95wcmb211.htm/, Retrieved Thu, 02 May 2024 14:04:48 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6004, Retrieved Thu, 02 May 2024 14:04:48 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact257

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Variance Reduction Matrix] [VRM P-index energ...] [2007-11-22 14:07:14] [4df98167d5cf79c69ce763f2d4ef5b15] [Current]
-    D    [Variance Reduction Matrix] [Variance Reductio...] [2008-11-29 09:08:16] [8545382734d98368249ce527c6558129]
-    D      [Variance Reduction Matrix] [VRM H1] [2008-11-29 09:10:10] [8545382734d98368249ce527c6558129]
-    D        [Variance Reduction Matrix] [VRM periode okt02...] [2008-11-29 10:30:45] [8545382734d98368249ce527c6558129]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
95,4
101,2
101,5
101,9
101,7
100,1
97,4
96,5
99,2
102,2
105,3
111,1
114,9
124,5
142,2
159,7
165,2
198,6
207,8
219,6
239,6
235,3
218,5
213,8
205,5
198,4
198,5
190,2
180,7
193,6
192,8
195,5
197,2
196,9
178,9
172,4
156,4
143,7
153,6
168,8
185,8
199,9
205,4
197,5
199,6
200,5
193,7
179,6
169,1
169,8
195,5
194,8
204,5
203,8
204,8
204,9
240,0
248,3
258,4
254,9

Tables (Output of Computation)





Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of compuational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 0 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6004&T=0

[TABLE]
[ROW][C]Summary of compuational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]0 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6004&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6004&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 compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Variance Reduction Matrix
V(Y[t],d=0,D=0)2124.68265254237Range163Trim Var.1662.69610062893
V(Y[t],d=1,D=0)123.675160724722Range53.1Trim Var.66.917793904209
V(Y[t],d=2,D=0)155.365943738657Range61.8Trim Var.82.6624849170437
V(Y[t],d=3,D=0)433.660695488721Range101.7Trim Var.216.729537254902
V(Y[t],d=0,D=1)2593.55134308511Range195.1Trim Var.1729.01698025552
V(Y[t],d=1,D=1)216.021137835338Range60.8Trim Var.137.165621951220
V(Y[t],d=2,D=1)190.813661835749Range61Trim Var.110.318051282051
V(Y[t],d=3,D=1)519.376131313131Range93.1Trim Var.312.62628879892
V(Y[t],d=0,D=2)6988.37094444444Range269.6Trim Var.5574.67935483871
V(Y[t],d=1,D=2)633.788907563025Range104.8Trim Var.415.833247311828
V(Y[t],d=2,D=2)410.916978609626Range92.3Trim Var.239.806482758621
V(Y[t],d=3,D=2)1006.00653409091Range125.4Trim Var.673.677192118226

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 2124.68265254237 & Range & 163 & Trim Var. & 1662.69610062893 \tabularnewline
V(Y[t],d=1,D=0) & 123.675160724722 & Range & 53.1 & Trim Var. & 66.917793904209 \tabularnewline
V(Y[t],d=2,D=0) & 155.365943738657 & Range & 61.8 & Trim Var. & 82.6624849170437 \tabularnewline
V(Y[t],d=3,D=0) & 433.660695488721 & Range & 101.7 & Trim Var. & 216.729537254902 \tabularnewline
V(Y[t],d=0,D=1) & 2593.55134308511 & Range & 195.1 & Trim Var. & 1729.01698025552 \tabularnewline
V(Y[t],d=1,D=1) & 216.021137835338 & Range & 60.8 & Trim Var. & 137.165621951220 \tabularnewline
V(Y[t],d=2,D=1) & 190.813661835749 & Range & 61 & Trim Var. & 110.318051282051 \tabularnewline
V(Y[t],d=3,D=1) & 519.376131313131 & Range & 93.1 & Trim Var. & 312.62628879892 \tabularnewline
V(Y[t],d=0,D=2) & 6988.37094444444 & Range & 269.6 & Trim Var. & 5574.67935483871 \tabularnewline
V(Y[t],d=1,D=2) & 633.788907563025 & Range & 104.8 & Trim Var. & 415.833247311828 \tabularnewline
V(Y[t],d=2,D=2) & 410.916978609626 & Range & 92.3 & Trim Var. & 239.806482758621 \tabularnewline
V(Y[t],d=3,D=2) & 1006.00653409091 & Range & 125.4 & Trim Var. & 673.677192118226 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6004&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]2124.68265254237[/C][C]Range[/C][C]163[/C][C]Trim Var.[/C][C]1662.69610062893[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]123.675160724722[/C][C]Range[/C][C]53.1[/C][C]Trim Var.[/C][C]66.917793904209[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]155.365943738657[/C][C]Range[/C][C]61.8[/C][C]Trim Var.[/C][C]82.6624849170437[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]433.660695488721[/C][C]Range[/C][C]101.7[/C][C]Trim Var.[/C][C]216.729537254902[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]2593.55134308511[/C][C]Range[/C][C]195.1[/C][C]Trim Var.[/C][C]1729.01698025552[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]216.021137835338[/C][C]Range[/C][C]60.8[/C][C]Trim Var.[/C][C]137.165621951220[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]190.813661835749[/C][C]Range[/C][C]61[/C][C]Trim Var.[/C][C]110.318051282051[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]519.376131313131[/C][C]Range[/C][C]93.1[/C][C]Trim Var.[/C][C]312.62628879892[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]6988.37094444444[/C][C]Range[/C][C]269.6[/C][C]Trim Var.[/C][C]5574.67935483871[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]633.788907563025[/C][C]Range[/C][C]104.8[/C][C]Trim Var.[/C][C]415.833247311828[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]410.916978609626[/C][C]Range[/C][C]92.3[/C][C]Trim Var.[/C][C]239.806482758621[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]1006.00653409091[/C][C]Range[/C][C]125.4[/C][C]Trim Var.[/C][C]673.677192118226[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6004&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6004&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:

Variance Reduction Matrix
V(Y[t],d=0,D=0)2124.68265254237Range163Trim Var.1662.69610062893
V(Y[t],d=1,D=0)123.675160724722Range53.1Trim Var.66.917793904209
V(Y[t],d=2,D=0)155.365943738657Range61.8Trim Var.82.6624849170437
V(Y[t],d=3,D=0)433.660695488721Range101.7Trim Var.216.729537254902
V(Y[t],d=0,D=1)2593.55134308511Range195.1Trim Var.1729.01698025552
V(Y[t],d=1,D=1)216.021137835338Range60.8Trim Var.137.165621951220
V(Y[t],d=2,D=1)190.813661835749Range61Trim Var.110.318051282051
V(Y[t],d=3,D=1)519.376131313131Range93.1Trim Var.312.62628879892
V(Y[t],d=0,D=2)6988.37094444444Range269.6Trim Var.5574.67935483871
V(Y[t],d=1,D=2)633.788907563025Range104.8Trim Var.415.833247311828
V(Y[t],d=2,D=2)410.916978609626Range92.3Trim Var.239.806482758621
V(Y[t],d=3,D=2)1006.00653409091Range125.4Trim Var.673.677192118226


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 12 ;
Parameters (R input):
par1 = 12 ;
R code (references can be found in the software module):
par1 <- as.numeric(par1)
n <- length(x)
sx <- sort(x)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Variance Reduction Matrix',6,TRUE)
a<-table.row.end(a)
for (bigd in 0:2) {
for (smalld in 0:3) {
mylabel <- 'V(Y[t],d='
mylabel <- paste(mylabel,as.character(smalld),sep='')
mylabel <- paste(mylabel,',D=',sep='')
mylabel <- paste(mylabel,as.character(bigd),sep='')
mylabel <- paste(mylabel,')',sep='')
a<-table.row.start(a)
a<-table.element(a,mylabel,header=TRUE)
myx <- x
if (smalld > 0) myx <- diff(x,lag=1,differences=smalld)
if (bigd > 0) myx <- diff(myx,lag=par1,differences=bigd)
a<-table.element(a,var(myx))
a<-table.element(a,'Range',header=TRUE)
a<-table.element(a,max(myx)-min(myx))
a<-table.element(a,'Trim Var.',header=TRUE)
smyx <- sort(myx)
sn <- length(smyx)
a<-table.element(a,var(smyx[smyx>quantile(smyx,0.05) & smyxa<-table.row.end(a)
}
}
a<-table.end(a)
table.save(a,file='mytable.tab')