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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 computationSat, 15 Dec 2012 08:35:20 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Dec/15/t1355578706d5ti7evu13hi5ib.htm/, Retrieved Tue, 30 Apr 2024 20:25:57 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=199908, Retrieved Tue, 30 Apr 2024 20:25:57 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact134

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [Univariate Data Series] [Identifying Integ...] [2009-11-22 12:08:06] [b98453cac15ba1066b407e146608df68]
- RMP         [Variance Reduction Matrix] [Births] [2010-11-29 09:39:41] [b98453cac15ba1066b407e146608df68]
- R PD          [Variance Reduction Matrix] [WS9 3.3 VRM matrix ] [2010-12-07 10:25:28] [afe9379cca749d06b3d6872e02cc47ed]
-    D            [Variance Reduction Matrix] [Apple Inc - VRM] [2010-12-14 16:19:52] [afe9379cca749d06b3d6872e02cc47ed]
- R PD                [Variance Reduction Matrix] [] [2012-12-15 13:35:20] [14d0a7ecb926325afa0eb6a607fbc7a0] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
26.81
28.24
27.58
27.98
27.84
27.49
26.97
27.71
27.46
27.04
28.00
27.32
26.36
26.15
25.94
24.00
24.32
23.10
22.92
23.56
22.17
22.36
19.86
20.07
19.21
19.99
20.47
21.17
21.25
21.18
21.21
21.11
21.94
22.56
23.23
19.50
19.32
19.00
18.98
19.88
19.48
19.52
19.52
19.75
19.64
20.23
20.40
20.91
21.95
21.83
22.27
21.99
21.66
20.32
20.62
20.28
20.79
22.86
22.59
23.29
21.87
21.52
22.00

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'Sir Maurice George Kendall' @ kendall.wessa.net

\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 & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=199908&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]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=199908&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=199908&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'Sir Maurice George Kendall' @ kendall.wessa.net






Variance Reduction Matrix
V(Y[t],d=0,D=0)8.41864244751664Range9.26Trim Var.6.59126821548822
V(Y[t],d=1,D=0)0.82309405076679Range5.8Trim Var.0.307479245283019
V(Y[t],d=2,D=0)1.84416841530055Range7.95Trim Var.0.89137206095791
V(Y[t],d=3,D=0)5.95729649717514Range12.4Trim Var.3.58555849056604
V(Y[t],d=0,D=1)2.33494192090395Range6.73Trim Var.1.52534577218728
V(Y[t],d=1,D=1)1.81701431911163Range8.27Trim Var.0.667516763425254
V(Y[t],d=2,D=1)4.01781890502117Range10.07Trim Var.2.18566681749623
V(Y[t],d=3,D=1)13.261896679198Range16.48Trim Var.7.5836923137255
V(Y[t],d=0,D=2)5.58659949874686Range11.46Trim Var.3.48488125490196
V(Y[t],d=1,D=2)5.52348022727273Range13.73Trim Var.2.18744575510204
V(Y[t],d=2,D=2)11.7867088888889Range17.78Trim Var.6.2933112244898
V(Y[t],d=3,D=2)38.2875044025157Range28.11Trim Var.22.0165998226951

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 8.41864244751664 & Range & 9.26 & Trim Var. & 6.59126821548822 \tabularnewline
V(Y[t],d=1,D=0) & 0.82309405076679 & Range & 5.8 & Trim Var. & 0.307479245283019 \tabularnewline
V(Y[t],d=2,D=0) & 1.84416841530055 & Range & 7.95 & Trim Var. & 0.89137206095791 \tabularnewline
V(Y[t],d=3,D=0) & 5.95729649717514 & Range & 12.4 & Trim Var. & 3.58555849056604 \tabularnewline
V(Y[t],d=0,D=1) & 2.33494192090395 & Range & 6.73 & Trim Var. & 1.52534577218728 \tabularnewline
V(Y[t],d=1,D=1) & 1.81701431911163 & Range & 8.27 & Trim Var. & 0.667516763425254 \tabularnewline
V(Y[t],d=2,D=1) & 4.01781890502117 & Range & 10.07 & Trim Var. & 2.18566681749623 \tabularnewline
V(Y[t],d=3,D=1) & 13.261896679198 & Range & 16.48 & Trim Var. & 7.5836923137255 \tabularnewline
V(Y[t],d=0,D=2) & 5.58659949874686 & Range & 11.46 & Trim Var. & 3.48488125490196 \tabularnewline
V(Y[t],d=1,D=2) & 5.52348022727273 & Range & 13.73 & Trim Var. & 2.18744575510204 \tabularnewline
V(Y[t],d=2,D=2) & 11.7867088888889 & Range & 17.78 & Trim Var. & 6.2933112244898 \tabularnewline
V(Y[t],d=3,D=2) & 38.2875044025157 & Range & 28.11 & Trim Var. & 22.0165998226951 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=199908&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]8.41864244751664[/C][C]Range[/C][C]9.26[/C][C]Trim Var.[/C][C]6.59126821548822[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]0.82309405076679[/C][C]Range[/C][C]5.8[/C][C]Trim Var.[/C][C]0.307479245283019[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]1.84416841530055[/C][C]Range[/C][C]7.95[/C][C]Trim Var.[/C][C]0.89137206095791[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]5.95729649717514[/C][C]Range[/C][C]12.4[/C][C]Trim Var.[/C][C]3.58555849056604[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]2.33494192090395[/C][C]Range[/C][C]6.73[/C][C]Trim Var.[/C][C]1.52534577218728[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]1.81701431911163[/C][C]Range[/C][C]8.27[/C][C]Trim Var.[/C][C]0.667516763425254[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]4.01781890502117[/C][C]Range[/C][C]10.07[/C][C]Trim Var.[/C][C]2.18566681749623[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]13.261896679198[/C][C]Range[/C][C]16.48[/C][C]Trim Var.[/C][C]7.5836923137255[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]5.58659949874686[/C][C]Range[/C][C]11.46[/C][C]Trim Var.[/C][C]3.48488125490196[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]5.52348022727273[/C][C]Range[/C][C]13.73[/C][C]Trim Var.[/C][C]2.18744575510204[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]11.7867088888889[/C][C]Range[/C][C]17.78[/C][C]Trim Var.[/C][C]6.2933112244898[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]38.2875044025157[/C][C]Range[/C][C]28.11[/C][C]Trim Var.[/C][C]22.0165998226951[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=199908&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=199908&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)8.41864244751664Range9.26Trim Var.6.59126821548822
V(Y[t],d=1,D=0)0.82309405076679Range5.8Trim Var.0.307479245283019
V(Y[t],d=2,D=0)1.84416841530055Range7.95Trim Var.0.89137206095791
V(Y[t],d=3,D=0)5.95729649717514Range12.4Trim Var.3.58555849056604
V(Y[t],d=0,D=1)2.33494192090395Range6.73Trim Var.1.52534577218728
V(Y[t],d=1,D=1)1.81701431911163Range8.27Trim Var.0.667516763425254
V(Y[t],d=2,D=1)4.01781890502117Range10.07Trim Var.2.18566681749623
V(Y[t],d=3,D=1)13.261896679198Range16.48Trim Var.7.5836923137255
V(Y[t],d=0,D=2)5.58659949874686Range11.46Trim Var.3.48488125490196
V(Y[t],d=1,D=2)5.52348022727273Range13.73Trim Var.2.18744575510204
V(Y[t],d=2,D=2)11.7867088888889Range17.78Trim Var.6.2933112244898
V(Y[t],d=3,D=2)38.2875044025157Range28.11Trim Var.22.0165998226951


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 3 ;
Parameters (R input):
par1 = 3 ;
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')