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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 computationSun, 20 Dec 2009 02:04:14 -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/2009/Dec/20/t12612999511v3p6blwhrql5h2.htm/, Retrieved Sat, 27 Apr 2024 10:39:04 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=69798, Retrieved Sat, 27 Apr 2024 10:39:04 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact152

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Variance Reduction Matrix] [Paper: Differenti...] [2009-12-20 09:04:14] [762da55b2e2304daaed24a7cc507d14d] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
90.2
90
88.8
85.8
84.2
80
77.8
76.8
86.4
89.2
86.2
84.6
83.2
83.2
82.6
79.8
77.2
74.8
73
73
83.6
85.6
84.8
84.2
83.4
84.6
84.6
83.8
81.2
79.6
78
78.2
88.8
92
91
91.2
90.4
91.8
92.2
90.2
88.6
87.8
86
87.2
97.6
101.2
100.4
100.2
100.2
103
104.2
104
102.4
101.8
101
102.2
114
118.4
118.8
117.2
117.2
118.4
118.8
117.2
114.4
112.6
111
110.8
120.2
124.4
123.4
121.2
119
119.8
120
118.4
115
113.4
111
111
121.6
126.2
125.8
124.8
122
123.2
124.2
120.8
116.8
114.8
111
109
119.8
124
121.6
118
115.8
116
115.8
114.4
112
110.2
107.4
108.2
117.6
121.4
119.8
115.6
112.6
113.2
112.2
110.8
108
105.2
102.4
101
110.8
116.8
113.8
108
104.4
105.2
105.4
103.2
100.6
97.8
95.8
95
104.8
110.4
106.4
102.2
98.4
98.4
98.6
96.2
92.4
91.4
88.4
87.8
97.6
104.2
100.2
97
92.8
92
93.4
92
89.6
88.6
87.2
86.2
96.8
102
102.6
100.6
94.2
94.2
95.2
95
94
92.2
91
91.2
103.4
105
104.6
103.8
101.8
102.4
103.8
103.4
102
101.8
100.2
101.4
113.8
116
115.6
113
109.4
111
112.4
112.2
111
108.8
107.4
108.6
118.8
122.2
122.6
122.2
118.8
119
118.2
117.8
116.8
114.6
113.4
113.8
124.2
125.8
125.6
122.4
119
119.4
118.6
118
116
114.8
114.6
114.6
124
125.2
124
117.6
113.2
111.4
112.2
109.8
106.4
105.2
102.2
99.8
111
113
108.4
105.4
102
102.8
103.4
101.6
98.6
98
93.8
95.6
105.6
106.8
103.6
101.2
100.4
103.2
105.6
106.6
107.2
107.4
104.8
107.2
117.4
119.4
116.2
112.8
111.6

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69798&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]3 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=69798&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69798&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 time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Variance Reduction Matrix
V(Y[t],d=0,D=0)167.789479892089Range53.2Trim Var.121.993754629449
V(Y[t],d=1,D=0)14.1124410295327Range18.8Trim Var.7.4580924287119
V(Y[t],d=2,D=0)19.2884640637450Range24.2Trim Var.9.38481428571429
V(Y[t],d=3,D=0)42.7217632128514Range35.8Trim Var.20.1562075592569
V(Y[t],d=0,D=1)53.11336791148Range34Trim Var.37.5032175613997
V(Y[t],d=1,D=1)1.73096164574616Range8.2Trim Var.0.929604651162789
V(Y[t],d=2,D=1)3.05629619211701Range12.2Trim Var.1.57706933275375
V(Y[t],d=3,D=1)9.19949296174165Range21.8Trim Var.4.90798476392948
V(Y[t],d=0,D=2)49.4625358155213Range35Trim Var.30.1723519846963
V(Y[t],d=1,D=2)4.23023108431872Range12.6Trim Var.2.19345656733161
V(Y[t],d=2,D=2)8.09986511247124Range18.6000000000000Trim Var.4.47649612251865
V(Y[t],d=3,D=2)24.2001746312684Range27.2Trim Var.13.6749046844983

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 167.789479892089 & Range & 53.2 & Trim Var. & 121.993754629449 \tabularnewline
V(Y[t],d=1,D=0) & 14.1124410295327 & Range & 18.8 & Trim Var. & 7.4580924287119 \tabularnewline
V(Y[t],d=2,D=0) & 19.2884640637450 & Range & 24.2 & Trim Var. & 9.38481428571429 \tabularnewline
V(Y[t],d=3,D=0) & 42.7217632128514 & Range & 35.8 & Trim Var. & 20.1562075592569 \tabularnewline
V(Y[t],d=0,D=1) & 53.11336791148 & Range & 34 & Trim Var. & 37.5032175613997 \tabularnewline
V(Y[t],d=1,D=1) & 1.73096164574616 & Range & 8.2 & Trim Var. & 0.929604651162789 \tabularnewline
V(Y[t],d=2,D=1) & 3.05629619211701 & Range & 12.2 & Trim Var. & 1.57706933275375 \tabularnewline
V(Y[t],d=3,D=1) & 9.19949296174165 & Range & 21.8 & Trim Var. & 4.90798476392948 \tabularnewline
V(Y[t],d=0,D=2) & 49.4625358155213 & Range & 35 & Trim Var. & 30.1723519846963 \tabularnewline
V(Y[t],d=1,D=2) & 4.23023108431872 & Range & 12.6 & Trim Var. & 2.19345656733161 \tabularnewline
V(Y[t],d=2,D=2) & 8.09986511247124 & Range & 18.6000000000000 & Trim Var. & 4.47649612251865 \tabularnewline
V(Y[t],d=3,D=2) & 24.2001746312684 & Range & 27.2 & Trim Var. & 13.6749046844983 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69798&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]167.789479892089[/C][C]Range[/C][C]53.2[/C][C]Trim Var.[/C][C]121.993754629449[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]14.1124410295327[/C][C]Range[/C][C]18.8[/C][C]Trim Var.[/C][C]7.4580924287119[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]19.2884640637450[/C][C]Range[/C][C]24.2[/C][C]Trim Var.[/C][C]9.38481428571429[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]42.7217632128514[/C][C]Range[/C][C]35.8[/C][C]Trim Var.[/C][C]20.1562075592569[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]53.11336791148[/C][C]Range[/C][C]34[/C][C]Trim Var.[/C][C]37.5032175613997[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]1.73096164574616[/C][C]Range[/C][C]8.2[/C][C]Trim Var.[/C][C]0.929604651162789[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]3.05629619211701[/C][C]Range[/C][C]12.2[/C][C]Trim Var.[/C][C]1.57706933275375[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]9.19949296174165[/C][C]Range[/C][C]21.8[/C][C]Trim Var.[/C][C]4.90798476392948[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]49.4625358155213[/C][C]Range[/C][C]35[/C][C]Trim Var.[/C][C]30.1723519846963[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]4.23023108431872[/C][C]Range[/C][C]12.6[/C][C]Trim Var.[/C][C]2.19345656733161[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]8.09986511247124[/C][C]Range[/C][C]18.6000000000000[/C][C]Trim Var.[/C][C]4.47649612251865[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]24.2001746312684[/C][C]Range[/C][C]27.2[/C][C]Trim Var.[/C][C]13.6749046844983[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69798&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69798&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)167.789479892089Range53.2Trim Var.121.993754629449
V(Y[t],d=1,D=0)14.1124410295327Range18.8Trim Var.7.4580924287119
V(Y[t],d=2,D=0)19.2884640637450Range24.2Trim Var.9.38481428571429
V(Y[t],d=3,D=0)42.7217632128514Range35.8Trim Var.20.1562075592569
V(Y[t],d=0,D=1)53.11336791148Range34Trim Var.37.5032175613997
V(Y[t],d=1,D=1)1.73096164574616Range8.2Trim Var.0.929604651162789
V(Y[t],d=2,D=1)3.05629619211701Range12.2Trim Var.1.57706933275375
V(Y[t],d=3,D=1)9.19949296174165Range21.8Trim Var.4.90798476392948
V(Y[t],d=0,D=2)49.4625358155213Range35Trim Var.30.1723519846963
V(Y[t],d=1,D=2)4.23023108431872Range12.6Trim Var.2.19345656733161
V(Y[t],d=2,D=2)8.09986511247124Range18.6000000000000Trim Var.4.47649612251865
V(Y[t],d=3,D=2)24.2001746312684Range27.2Trim Var.13.6749046844983


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')