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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_variancereduction.wasp
Title produced by softwareVariance Reduction Matrix
Date of computationThu, 18 Dec 2008 04:26:21 -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/2008/Dec/18/t1229599623cd8f0yrozjwqgkr.htm/, Retrieved Sun, 12 May 2024 04:29:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=34656, Retrieved Sun, 12 May 2024 04:29:10 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact199

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Mean Plot] [Gilliam Schoorel] [2008-11-06 14:07:56] [666bda00bbd072dde5655a1423b1377b]
- RM D  [Variance Reduction Matrix] [VRM suiker] [2008-12-09 16:07:08] [f77c9ab3b413812d7baee6b7ec69a15d]
-    D      [Variance Reduction Matrix] [VRM chocpasta zon...] [2008-12-18 11:26:21] [3fc0b50a130253095e963177b0139835] [Current]
-  M D        [Variance Reduction Matrix] [Variance Reductio...] [2010-12-06 13:25:13] [ff7c1e95cf99a1dae07ec89975494dde]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
101.73
101.63
101.43
101.34
101.01
100.89
100.93
100.77
100.3
99.86
99.71
99.93
99.88
99.92
99.87
99.63
100.05
99.88
100.11
100.05
100.07
100.2
100.21
99.76
99.41
99.24
99.65
99.7
99.79
99.84
101
101.62
101.98
101.46
102.28
102.14
102.02
102.21
101.61
102.38
102.19
102.04
101.76
101.9
102.01
102.37
103.04
103.42
103.76
104.41
104.75
104.28
103.89
104.09
103.8
105.03
105.86
106.04
106.03
106.13
107.21
107.66
108.08
108.76
108.26
108.71
108.65
108.61
108.86
109.54
108.22
108.77
109.9
110.13
109.6
110.42
110.6
109.73
110.72
111.08
111.14
111.01
110.56
111.57

Tables (Output of Computation)





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

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34656&T=0

[TABLE]
[ROW][C]Summary of computational 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]1 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=34656&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34656&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Variance Reduction Matrix
V(Y[t],d=0,D=0)15.5147756741251Range12.33Trim Var.12.7436261569789
V(Y[t],d=1,D=0)0.231444225683221Range2.55000000000001Trim Var.0.132227473363775
V(Y[t],d=2,D=0)0.479628078891902Range3.87000000000002Trim Var.0.242845931142412
V(Y[t],d=3,D=0)1.39038694444445Range6.36Trim Var.0.67000845070423
V(Y[t],d=0,D=1)2.70360749217527Range6.70000000000002Trim Var.1.78417142857143
V(Y[t],d=1,D=1)0.391973682092556Range2.59000000000000Trim Var.0.251199539170508
V(Y[t],d=2,D=1)0.860546915113872Range4.54999999999995Trim Var.0.501143019566371
V(Y[t],d=3,D=1)2.62244475703325Range7.38999999999987Trim Var.1.57200524590166
V(Y[t],d=0,D=2)3.1549765819209Range7.41999999999997Trim Var.2.25560111809923
V(Y[t],d=1,D=2)1.13938918760959Range4.75999999999999Trim Var.0.707574963715532
V(Y[t],d=2,D=2)2.42911518451301Range7.4Trim Var.1.60309573906486
V(Y[t],d=3,D=2)7.24785344611531Range11.71Trim Var.4.50086901960788

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 15.5147756741251 & Range & 12.33 & Trim Var. & 12.7436261569789 \tabularnewline
V(Y[t],d=1,D=0) & 0.231444225683221 & Range & 2.55000000000001 & Trim Var. & 0.132227473363775 \tabularnewline
V(Y[t],d=2,D=0) & 0.479628078891902 & Range & 3.87000000000002 & Trim Var. & 0.242845931142412 \tabularnewline
V(Y[t],d=3,D=0) & 1.39038694444445 & Range & 6.36 & Trim Var. & 0.67000845070423 \tabularnewline
V(Y[t],d=0,D=1) & 2.70360749217527 & Range & 6.70000000000002 & Trim Var. & 1.78417142857143 \tabularnewline
V(Y[t],d=1,D=1) & 0.391973682092556 & Range & 2.59000000000000 & Trim Var. & 0.251199539170508 \tabularnewline
V(Y[t],d=2,D=1) & 0.860546915113872 & Range & 4.54999999999995 & Trim Var. & 0.501143019566371 \tabularnewline
V(Y[t],d=3,D=1) & 2.62244475703325 & Range & 7.38999999999987 & Trim Var. & 1.57200524590166 \tabularnewline
V(Y[t],d=0,D=2) & 3.1549765819209 & Range & 7.41999999999997 & Trim Var. & 2.25560111809923 \tabularnewline
V(Y[t],d=1,D=2) & 1.13938918760959 & Range & 4.75999999999999 & Trim Var. & 0.707574963715532 \tabularnewline
V(Y[t],d=2,D=2) & 2.42911518451301 & Range & 7.4 & Trim Var. & 1.60309573906486 \tabularnewline
V(Y[t],d=3,D=2) & 7.24785344611531 & Range & 11.71 & Trim Var. & 4.50086901960788 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34656&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]15.5147756741251[/C][C]Range[/C][C]12.33[/C][C]Trim Var.[/C][C]12.7436261569789[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]0.231444225683221[/C][C]Range[/C][C]2.55000000000001[/C][C]Trim Var.[/C][C]0.132227473363775[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]0.479628078891902[/C][C]Range[/C][C]3.87000000000002[/C][C]Trim Var.[/C][C]0.242845931142412[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]1.39038694444445[/C][C]Range[/C][C]6.36[/C][C]Trim Var.[/C][C]0.67000845070423[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]2.70360749217527[/C][C]Range[/C][C]6.70000000000002[/C][C]Trim Var.[/C][C]1.78417142857143[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]0.391973682092556[/C][C]Range[/C][C]2.59000000000000[/C][C]Trim Var.[/C][C]0.251199539170508[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]0.860546915113872[/C][C]Range[/C][C]4.54999999999995[/C][C]Trim Var.[/C][C]0.501143019566371[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]2.62244475703325[/C][C]Range[/C][C]7.38999999999987[/C][C]Trim Var.[/C][C]1.57200524590166[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]3.1549765819209[/C][C]Range[/C][C]7.41999999999997[/C][C]Trim Var.[/C][C]2.25560111809923[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]1.13938918760959[/C][C]Range[/C][C]4.75999999999999[/C][C]Trim Var.[/C][C]0.707574963715532[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]2.42911518451301[/C][C]Range[/C][C]7.4[/C][C]Trim Var.[/C][C]1.60309573906486[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]7.24785344611531[/C][C]Range[/C][C]11.71[/C][C]Trim Var.[/C][C]4.50086901960788[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=34656&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34656&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)15.5147756741251Range12.33Trim Var.12.7436261569789
V(Y[t],d=1,D=0)0.231444225683221Range2.55000000000001Trim Var.0.132227473363775
V(Y[t],d=2,D=0)0.479628078891902Range3.87000000000002Trim Var.0.242845931142412
V(Y[t],d=3,D=0)1.39038694444445Range6.36Trim Var.0.67000845070423
V(Y[t],d=0,D=1)2.70360749217527Range6.70000000000002Trim Var.1.78417142857143
V(Y[t],d=1,D=1)0.391973682092556Range2.59000000000000Trim Var.0.251199539170508
V(Y[t],d=2,D=1)0.860546915113872Range4.54999999999995Trim Var.0.501143019566371
V(Y[t],d=3,D=1)2.62244475703325Range7.38999999999987Trim Var.1.57200524590166
V(Y[t],d=0,D=2)3.1549765819209Range7.41999999999997Trim Var.2.25560111809923
V(Y[t],d=1,D=2)1.13938918760959Range4.75999999999999Trim Var.0.707574963715532
V(Y[t],d=2,D=2)2.42911518451301Range7.4Trim Var.1.60309573906486
V(Y[t],d=3,D=2)7.24785344611531Range11.71Trim Var.4.50086901960788


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')