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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, 02 Dec 2010 14:02:46 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/02/t1291298446b3d0ph965fd4wao.htm/, Retrieved Sun, 05 May 2024 10:22:52 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=104297, Retrieved Sun, 05 May 2024 10:22:52 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact129

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       [Spectral Analysis] [Identifying Integ...] [2009-11-22 12:38:17] [b98453cac15ba1066b407e146608df68]
-    D        [Spectral Analysis] [spectrumanalyse] [2009-11-28 09:48:21] [7773f496f69461f4a67891f0ef752622]
-   PD          [Spectral Analysis] [koffie en thee] [2009-12-16 20:15:20] [7773f496f69461f4a67891f0ef752622]
- RMPD            [Variance Reduction Matrix] [thee] [2009-12-16 20:39:57] [7773f496f69461f4a67891f0ef752622]
-    D              [Variance Reduction Matrix] [Appelen Jonagold ...] [2009-12-17 16:45:59] [7773f496f69461f4a67891f0ef752622]
-    D                  [Variance Reduction Matrix] [Variance reductio...] [2010-12-02 14:02:46] [2fa539864aa87c5da4977c85c6885fac] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1.25 
1.23 
1.2 
1.15 
1.13 
1.17 
1.22 
1.21 
1.15 
1.24 
1.16 
1.3 
1.3 
1.26 
1.29 
1.29 
1.35 
1.35 
1.45 
1.43 
1.43 
1.41 
1.46 
1.78 
1.79 
1.66 
1.56 
1.53 
1.47 
1.47 
1.45 
1.41 
1.45 
1.46 
1.38 
1.45 
1.48 
1.48 
1.51 
1.45 
1.42 
1.43 
1.43 
1.44 
1.41 
1.35 
1.43 
1.72 
1.63 
1.57 
1.47 
1.39 
1.34 
1.28 
1.26 
1.26

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 Ronald Aylmer Fisher' @ 193.190.124.24

\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 Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=104297&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 Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=104297&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=104297&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 Ronald Aylmer Fisher' @ 193.190.124.24






Variance Reduction Matrix
V(Y[t],d=0,D=0)0.023227012987013Range0.66Trim Var.0.0137500408163265
V(Y[t],d=1,D=0)0.00649070707070707Range0.45Trim Var.0.00216811224489796
V(Y[t],d=2,D=0)0.0121432564640112Range0.65Trim Var.0.00442819148936171
V(Y[t],d=3,D=0)0.0341131349782294Range1Trim Var.0.0125271045328400
V(Y[t],d=0,D=1)0.00649070707070707Range0.45Trim Var.0.00216811224489796
V(Y[t],d=1,D=1)0.0121432564640112Range0.65Trim Var.0.00442819148936171
V(Y[t],d=2,D=1)0.0341131349782294Range1Trim Var.0.0125271045328400
V(Y[t],d=3,D=1)0.110754864253394Range1.78Trim Var.0.0438599033816426
V(Y[t],d=0,D=2)0.0121432564640112Range0.65Trim Var.0.00442819148936171
V(Y[t],d=1,D=2)0.0341131349782294Range1Trim Var.0.0125271045328400
V(Y[t],d=2,D=2)0.110754864253394Range1.78Trim Var.0.0438599033816426
V(Y[t],d=3,D=2)0.38434737254902Range3.14000000000000Trim Var.0.170060909090909

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 0.023227012987013 & Range & 0.66 & Trim Var. & 0.0137500408163265 \tabularnewline
V(Y[t],d=1,D=0) & 0.00649070707070707 & Range & 0.45 & Trim Var. & 0.00216811224489796 \tabularnewline
V(Y[t],d=2,D=0) & 0.0121432564640112 & Range & 0.65 & Trim Var. & 0.00442819148936171 \tabularnewline
V(Y[t],d=3,D=0) & 0.0341131349782294 & Range & 1 & Trim Var. & 0.0125271045328400 \tabularnewline
V(Y[t],d=0,D=1) & 0.00649070707070707 & Range & 0.45 & Trim Var. & 0.00216811224489796 \tabularnewline
V(Y[t],d=1,D=1) & 0.0121432564640112 & Range & 0.65 & Trim Var. & 0.00442819148936171 \tabularnewline
V(Y[t],d=2,D=1) & 0.0341131349782294 & Range & 1 & Trim Var. & 0.0125271045328400 \tabularnewline
V(Y[t],d=3,D=1) & 0.110754864253394 & Range & 1.78 & Trim Var. & 0.0438599033816426 \tabularnewline
V(Y[t],d=0,D=2) & 0.0121432564640112 & Range & 0.65 & Trim Var. & 0.00442819148936171 \tabularnewline
V(Y[t],d=1,D=2) & 0.0341131349782294 & Range & 1 & Trim Var. & 0.0125271045328400 \tabularnewline
V(Y[t],d=2,D=2) & 0.110754864253394 & Range & 1.78 & Trim Var. & 0.0438599033816426 \tabularnewline
V(Y[t],d=3,D=2) & 0.38434737254902 & Range & 3.14000000000000 & Trim Var. & 0.170060909090909 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=104297&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]0.023227012987013[/C][C]Range[/C][C]0.66[/C][C]Trim Var.[/C][C]0.0137500408163265[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]0.00649070707070707[/C][C]Range[/C][C]0.45[/C][C]Trim Var.[/C][C]0.00216811224489796[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]0.0121432564640112[/C][C]Range[/C][C]0.65[/C][C]Trim Var.[/C][C]0.00442819148936171[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]0.0341131349782294[/C][C]Range[/C][C]1[/C][C]Trim Var.[/C][C]0.0125271045328400[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]0.00649070707070707[/C][C]Range[/C][C]0.45[/C][C]Trim Var.[/C][C]0.00216811224489796[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]0.0121432564640112[/C][C]Range[/C][C]0.65[/C][C]Trim Var.[/C][C]0.00442819148936171[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]0.0341131349782294[/C][C]Range[/C][C]1[/C][C]Trim Var.[/C][C]0.0125271045328400[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]0.110754864253394[/C][C]Range[/C][C]1.78[/C][C]Trim Var.[/C][C]0.0438599033816426[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]0.0121432564640112[/C][C]Range[/C][C]0.65[/C][C]Trim Var.[/C][C]0.00442819148936171[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]0.0341131349782294[/C][C]Range[/C][C]1[/C][C]Trim Var.[/C][C]0.0125271045328400[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]0.110754864253394[/C][C]Range[/C][C]1.78[/C][C]Trim Var.[/C][C]0.0438599033816426[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]0.38434737254902[/C][C]Range[/C][C]3.14000000000000[/C][C]Trim Var.[/C][C]0.170060909090909[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=104297&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=104297&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)0.023227012987013Range0.66Trim Var.0.0137500408163265
V(Y[t],d=1,D=0)0.00649070707070707Range0.45Trim Var.0.00216811224489796
V(Y[t],d=2,D=0)0.0121432564640112Range0.65Trim Var.0.00442819148936171
V(Y[t],d=3,D=0)0.0341131349782294Range1Trim Var.0.0125271045328400
V(Y[t],d=0,D=1)0.00649070707070707Range0.45Trim Var.0.00216811224489796
V(Y[t],d=1,D=1)0.0121432564640112Range0.65Trim Var.0.00442819148936171
V(Y[t],d=2,D=1)0.0341131349782294Range1Trim Var.0.0125271045328400
V(Y[t],d=3,D=1)0.110754864253394Range1.78Trim Var.0.0438599033816426
V(Y[t],d=0,D=2)0.0121432564640112Range0.65Trim Var.0.00442819148936171
V(Y[t],d=1,D=2)0.0341131349782294Range1Trim Var.0.0125271045328400
V(Y[t],d=2,D=2)0.110754864253394Range1.78Trim Var.0.0438599033816426
V(Y[t],d=3,D=2)0.38434737254902Range3.14000000000000Trim Var.0.170060909090909


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ;
Parameters (R input):
par1 = 1 ;
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')