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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, 08 Dec 2008 11:17:24 -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/08/t1228760273cvpwo18q42zjikg.htm/, Retrieved Thu, 16 May 2024 04:25:12 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=30641, Retrieved Thu, 16 May 2024 04:25:12 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact181

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [Standard Deviation-Mean Plot] [SDMP] [2008-12-05 07:29:02] [c5a66f1c8528a963efc2b82a8519f117]
-    D    [Standard Deviation-Mean Plot] [SDMP] [2008-12-05 13:12:40] [c5a66f1c8528a963efc2b82a8519f117]
-    D      [Standard Deviation-Mean Plot] [SDMP woninghuur] [2008-12-08 18:10:50] [c5a66f1c8528a963efc2b82a8519f117]
- RM D          [Variance Reduction Matrix] [VRM - woninghuur] [2008-12-08 18:17:24] [b4fc5040f26b33db57f84cfb8d1d2b82] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
106.6
106.8
107
107.1
107.3
107.4
107.6
107.7
107.9
108.2
108.3
108.5
108.92
109.23
109.41
109.65
109.91
110.01
110.2
110.49
110.57
110.72
110.94
111.09
111.28
111.41
111.62
111.76
111.89
112.04
112.12
112.3
112.47
112.59
112.78
112.73
112.99
113.1
113.33
113.38
113.68
113.65
113.81
113.88
114.02
114.25
114.28
114.38
114.73
114.97
115.05
115.29
115.37
115.54
115.76
115.92
116.02
116.21
116.26
116.51

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=30641&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=30641&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30641&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)8.36626946327684Range9.91000000000001Trim Var.6.73432763801538
V(Y[t],d=1,D=0)0.0077026884862654Range0.469999999999999Trim Var.0.00431117561683599
V(Y[t],d=2,D=0)0.0188887174833637Range0.64Trim Var.0.0126469079939667
V(Y[t],d=3,D=0)0.0613624686716794Range1.13000000000001Trim Var.0.040028078431372
V(Y[t],d=0,D=1)0.132893218085107Range1.28999999999999Trim Var.0.101464576074333
V(Y[t],d=1,D=1)0.0147637372802966Range0.430000000000007Trim Var.0.0106512195121956
V(Y[t],d=2,D=1)0.0381014492753638Range0.830000000000041Trim Var.0.0240964102564108
V(Y[t],d=3,D=1)0.129324949494954Range1.58000000000008Trim Var.0.0788902834008084
V(Y[t],d=0,D=2)0.179637142857145Range1.46000000000001Trim Var.0.135361189516130
V(Y[t],d=1,D=2)0.040325546218489Range0.770000000000039Trim Var.0.0287479569892486
V(Y[t],d=2,D=2)0.113970499108739Range1.44000000000008Trim Var.0.0751458620689668
V(Y[t],d=3,D=2)0.396243939393955Range2.61000000000013Trim Var.0.252690886699507

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 8.36626946327684 & Range & 9.91000000000001 & Trim Var. & 6.73432763801538 \tabularnewline
V(Y[t],d=1,D=0) & 0.0077026884862654 & Range & 0.469999999999999 & Trim Var. & 0.00431117561683599 \tabularnewline
V(Y[t],d=2,D=0) & 0.0188887174833637 & Range & 0.64 & Trim Var. & 0.0126469079939667 \tabularnewline
V(Y[t],d=3,D=0) & 0.0613624686716794 & Range & 1.13000000000001 & Trim Var. & 0.040028078431372 \tabularnewline
V(Y[t],d=0,D=1) & 0.132893218085107 & Range & 1.28999999999999 & Trim Var. & 0.101464576074333 \tabularnewline
V(Y[t],d=1,D=1) & 0.0147637372802966 & Range & 0.430000000000007 & Trim Var. & 0.0106512195121956 \tabularnewline
V(Y[t],d=2,D=1) & 0.0381014492753638 & Range & 0.830000000000041 & Trim Var. & 0.0240964102564108 \tabularnewline
V(Y[t],d=3,D=1) & 0.129324949494954 & Range & 1.58000000000008 & Trim Var. & 0.0788902834008084 \tabularnewline
V(Y[t],d=0,D=2) & 0.179637142857145 & Range & 1.46000000000001 & Trim Var. & 0.135361189516130 \tabularnewline
V(Y[t],d=1,D=2) & 0.040325546218489 & Range & 0.770000000000039 & Trim Var. & 0.0287479569892486 \tabularnewline
V(Y[t],d=2,D=2) & 0.113970499108739 & Range & 1.44000000000008 & Trim Var. & 0.0751458620689668 \tabularnewline
V(Y[t],d=3,D=2) & 0.396243939393955 & Range & 2.61000000000013 & Trim Var. & 0.252690886699507 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30641&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]8.36626946327684[/C][C]Range[/C][C]9.91000000000001[/C][C]Trim Var.[/C][C]6.73432763801538[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]0.0077026884862654[/C][C]Range[/C][C]0.469999999999999[/C][C]Trim Var.[/C][C]0.00431117561683599[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]0.0188887174833637[/C][C]Range[/C][C]0.64[/C][C]Trim Var.[/C][C]0.0126469079939667[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]0.0613624686716794[/C][C]Range[/C][C]1.13000000000001[/C][C]Trim Var.[/C][C]0.040028078431372[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]0.132893218085107[/C][C]Range[/C][C]1.28999999999999[/C][C]Trim Var.[/C][C]0.101464576074333[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]0.0147637372802966[/C][C]Range[/C][C]0.430000000000007[/C][C]Trim Var.[/C][C]0.0106512195121956[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]0.0381014492753638[/C][C]Range[/C][C]0.830000000000041[/C][C]Trim Var.[/C][C]0.0240964102564108[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]0.129324949494954[/C][C]Range[/C][C]1.58000000000008[/C][C]Trim Var.[/C][C]0.0788902834008084[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]0.179637142857145[/C][C]Range[/C][C]1.46000000000001[/C][C]Trim Var.[/C][C]0.135361189516130[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]0.040325546218489[/C][C]Range[/C][C]0.770000000000039[/C][C]Trim Var.[/C][C]0.0287479569892486[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]0.113970499108739[/C][C]Range[/C][C]1.44000000000008[/C][C]Trim Var.[/C][C]0.0751458620689668[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]0.396243939393955[/C][C]Range[/C][C]2.61000000000013[/C][C]Trim Var.[/C][C]0.252690886699507[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30641&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30641&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)8.36626946327684Range9.91000000000001Trim Var.6.73432763801538
V(Y[t],d=1,D=0)0.0077026884862654Range0.469999999999999Trim Var.0.00431117561683599
V(Y[t],d=2,D=0)0.0188887174833637Range0.64Trim Var.0.0126469079939667
V(Y[t],d=3,D=0)0.0613624686716794Range1.13000000000001Trim Var.0.040028078431372
V(Y[t],d=0,D=1)0.132893218085107Range1.28999999999999Trim Var.0.101464576074333
V(Y[t],d=1,D=1)0.0147637372802966Range0.430000000000007Trim Var.0.0106512195121956
V(Y[t],d=2,D=1)0.0381014492753638Range0.830000000000041Trim Var.0.0240964102564108
V(Y[t],d=3,D=1)0.129324949494954Range1.58000000000008Trim Var.0.0788902834008084
V(Y[t],d=0,D=2)0.179637142857145Range1.46000000000001Trim Var.0.135361189516130
V(Y[t],d=1,D=2)0.040325546218489Range0.770000000000039Trim Var.0.0287479569892486
V(Y[t],d=2,D=2)0.113970499108739Range1.44000000000008Trim Var.0.0751458620689668
V(Y[t],d=3,D=2)0.396243939393955Range2.61000000000013Trim Var.0.252690886699507


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')