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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 computationMon, 20 Dec 2010 13:53:52 +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/20/t1292853127ies58tl9zydiyae.htm/, Retrieved Fri, 03 May 2024 15:43:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=112947, Retrieved Fri, 03 May 2024 15:43:05 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact123

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]
-   PD            [Variance Reduction Matrix] [VRM Jenever] [2010-12-20 13:53:52] [47bfda5353cd53c1cf7ea7aa9038654a] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
11,04
11,02
11,03
11,17
11,19
11,15
11,13
11,06
11,01
11,03
10,99
10,94
11,00
11,06
11,06
11,05
11,04
11,15
11,20
11,16
11,30
11,23
11,25
11,25
11,12
11,14
11,17
11,25
11,27
11,34
11,39
11,44
11,46
11,49
11,51
11,48
11,49
11,52
11,56
11,58
11,58
11,58
11,60
11,62
11,62
11,64
11,67
11,66
11,72
11,82
11,90
12,04
12,08
12,15
12,19
12,22
12,23
12,25
12,26
12,27
12,34
12,38
12,42
12,43
12,48
12,50
12,50
12,49
12,46
12,45
12,45
12,38
12,42

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'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112947&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112947&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112947&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'George Udny Yule' @ 72.249.76.132






Variance Reduction Matrix
V(Y[t],d=0,D=0)0.272739916286149Range1.56Trim Var.0.233902740384615
V(Y[t],d=1,D=0)0.00235422535211268Range0.270000000000001Trim Var.0.00109481646825397
V(Y[t],d=2,D=0)0.00402498993963784Range0.390000000000001Trim Var.0.00177700972862261
V(Y[t],d=3,D=0)0.0118508488612837Range0.690000000000001Trim Var.0.00445058170280277
V(Y[t],d=0,D=1)0.0355337158469945Range0.77Trim Var.0.0224052975326560
V(Y[t],d=1,D=1)0.00494169491525424Range0.380000000000003Trim Var.0.00260143256464009
V(Y[t],d=2,D=1)0.00933611922852132Range0.5Trim Var.0.00484332365747458
V(Y[t],d=3,D=1)0.0281238959467634Range0.870000000000001Trim Var.0.0136363122171945
V(Y[t],d=0,D=2)0.069868962585034Range0.999999999999998Trim Var.0.0457133565621371
V(Y[t],d=1,D=2)0.0133955673758865Range0.640000000000002Trim Var.0.00562189314750284
V(Y[t],d=2,D=2)0.0272448658649397Range0.869999999999997Trim Var.0.0127137804878047
V(Y[t],d=3,D=2)0.0848573913043474Range1.62000000000000Trim Var.0.0368137820512817

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 0.272739916286149 & Range & 1.56 & Trim Var. & 0.233902740384615 \tabularnewline
V(Y[t],d=1,D=0) & 0.00235422535211268 & Range & 0.270000000000001 & Trim Var. & 0.00109481646825397 \tabularnewline
V(Y[t],d=2,D=0) & 0.00402498993963784 & Range & 0.390000000000001 & Trim Var. & 0.00177700972862261 \tabularnewline
V(Y[t],d=3,D=0) & 0.0118508488612837 & Range & 0.690000000000001 & Trim Var. & 0.00445058170280277 \tabularnewline
V(Y[t],d=0,D=1) & 0.0355337158469945 & Range & 0.77 & Trim Var. & 0.0224052975326560 \tabularnewline
V(Y[t],d=1,D=1) & 0.00494169491525424 & Range & 0.380000000000003 & Trim Var. & 0.00260143256464009 \tabularnewline
V(Y[t],d=2,D=1) & 0.00933611922852132 & Range & 0.5 & Trim Var. & 0.00484332365747458 \tabularnewline
V(Y[t],d=3,D=1) & 0.0281238959467634 & Range & 0.870000000000001 & Trim Var. & 0.0136363122171945 \tabularnewline
V(Y[t],d=0,D=2) & 0.069868962585034 & Range & 0.999999999999998 & Trim Var. & 0.0457133565621371 \tabularnewline
V(Y[t],d=1,D=2) & 0.0133955673758865 & Range & 0.640000000000002 & Trim Var. & 0.00562189314750284 \tabularnewline
V(Y[t],d=2,D=2) & 0.0272448658649397 & Range & 0.869999999999997 & Trim Var. & 0.0127137804878047 \tabularnewline
V(Y[t],d=3,D=2) & 0.0848573913043474 & Range & 1.62000000000000 & Trim Var. & 0.0368137820512817 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112947&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]0.272739916286149[/C][C]Range[/C][C]1.56[/C][C]Trim Var.[/C][C]0.233902740384615[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]0.00235422535211268[/C][C]Range[/C][C]0.270000000000001[/C][C]Trim Var.[/C][C]0.00109481646825397[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]0.00402498993963784[/C][C]Range[/C][C]0.390000000000001[/C][C]Trim Var.[/C][C]0.00177700972862261[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]0.0118508488612837[/C][C]Range[/C][C]0.690000000000001[/C][C]Trim Var.[/C][C]0.00445058170280277[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]0.0355337158469945[/C][C]Range[/C][C]0.77[/C][C]Trim Var.[/C][C]0.0224052975326560[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]0.00494169491525424[/C][C]Range[/C][C]0.380000000000003[/C][C]Trim Var.[/C][C]0.00260143256464009[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]0.00933611922852132[/C][C]Range[/C][C]0.5[/C][C]Trim Var.[/C][C]0.00484332365747458[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]0.0281238959467634[/C][C]Range[/C][C]0.870000000000001[/C][C]Trim Var.[/C][C]0.0136363122171945[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]0.069868962585034[/C][C]Range[/C][C]0.999999999999998[/C][C]Trim Var.[/C][C]0.0457133565621371[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]0.0133955673758865[/C][C]Range[/C][C]0.640000000000002[/C][C]Trim Var.[/C][C]0.00562189314750284[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]0.0272448658649397[/C][C]Range[/C][C]0.869999999999997[/C][C]Trim Var.[/C][C]0.0127137804878047[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]0.0848573913043474[/C][C]Range[/C][C]1.62000000000000[/C][C]Trim Var.[/C][C]0.0368137820512817[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112947&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112947&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)0.272739916286149Range1.56Trim Var.0.233902740384615
V(Y[t],d=1,D=0)0.00235422535211268Range0.270000000000001Trim Var.0.00109481646825397
V(Y[t],d=2,D=0)0.00402498993963784Range0.390000000000001Trim Var.0.00177700972862261
V(Y[t],d=3,D=0)0.0118508488612837Range0.690000000000001Trim Var.0.00445058170280277
V(Y[t],d=0,D=1)0.0355337158469945Range0.77Trim Var.0.0224052975326560
V(Y[t],d=1,D=1)0.00494169491525424Range0.380000000000003Trim Var.0.00260143256464009
V(Y[t],d=2,D=1)0.00933611922852132Range0.5Trim Var.0.00484332365747458
V(Y[t],d=3,D=1)0.0281238959467634Range0.870000000000001Trim Var.0.0136363122171945
V(Y[t],d=0,D=2)0.069868962585034Range0.999999999999998Trim Var.0.0457133565621371
V(Y[t],d=1,D=2)0.0133955673758865Range0.640000000000002Trim Var.0.00562189314750284
V(Y[t],d=2,D=2)0.0272448658649397Range0.869999999999997Trim Var.0.0127137804878047
V(Y[t],d=3,D=2)0.0848573913043474Range1.62000000000000Trim Var.0.0368137820512817


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')