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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, 23 Nov 2009 08:40:52 -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/Nov/23/t1258990950vdstnpwxrddvny2.htm/, Retrieved Fri, 03 May 2024 06:04:18 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=58799, Retrieved Fri, 03 May 2024 06:04:18 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact174

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       [Variance Reduction Matrix] [Identifying Integ...] [2009-11-22 12:29:54] [b98453cac15ba1066b407e146608df68]
-    D          [Variance Reduction Matrix] [] [2009-11-23 15:40:52] [2b679e8ec54382eeb0ec0b6bb527570a] [Current]
-    D            [Variance Reduction Matrix] [] [2009-11-28 11:16:12] [5d885a68c2332cc44f6191ec94766bfa]
-    D            [Variance Reduction Matrix] [VRM] [2009-12-04 12:09:51] [74be16979710d4c4e7c6647856088456]
- R  D            [Variance Reduction Matrix] [] [2009-12-04 15:02:32] [fa71ec4c741ffec745cb91dcbd756720]
-   PD            [Variance Reduction Matrix] [] [2009-12-20 09:00:19] [5d885a68c2332cc44f6191ec94766bfa]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
100.03
100.25
99.6
100.16
100.49
99.72
100.14
98.48
100.38
101.45
98.42
98.6
100.06
98.62
100.84
100.02
97.95
98.32
98.27
97.22
99.28
100.38
99.02
100.32
99.81
100.6
101.19
100.47
101.77
102.32
102.39
101.16
100.63
101.48
101.44
100.09
100.7
100.78
99.81
98.45
98.49
97.48
97.91
96.94
98.53
96.82
95.76
95.27
97.32
96.68
97.87
97.42
97.94
99.52
100.99
99.92
101.97
101.58
99.54
100.83

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 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 & 0 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=58799&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]0 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=58799&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=58799&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 time0 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Variance Reduction Matrix
V(Y[t],d=0,D=0)2.7035745480226Range7.12Trim Var.1.83315206149546
V(Y[t],d=1,D=0)1.47251987142022Range5.25Trim Var.0.984487782805427
V(Y[t],d=2,D=0)3.88400632183907Range7.76Trim Var.2.88805248868777
V(Y[t],d=3,D=0)11.9586022556391Range14.01Trim Var.8.62380141176467
V(Y[t],d=0,D=1)8.40456578014184Range11.24Trim Var.5.99220116144019
V(Y[t],d=1,D=1)2.31103570767807Range6.01999999999998Trim Var.1.49695743902438
V(Y[t],d=2,D=1)5.46998106280191Range9.21000000000002Trim Var.3.53687589743587
V(Y[t],d=3,D=1)16.4457790909090Range16.5200000000000Trim Var.10.1872862348177
V(Y[t],d=0,D=2)30.9677577777778Range19.22Trim Var.23.7409415322581
V(Y[t],d=1,D=2)6.94435495798318Range10.4000000000000Trim Var.4.64649655913978
V(Y[t],d=2,D=2)15.5646624777183Range15.2500000000000Trim Var.10.7377747126436
V(Y[t],d=3,D=2)45.2286085227271Range27.2600000000000Trim Var.30.0520591133004

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 2.7035745480226 & Range & 7.12 & Trim Var. & 1.83315206149546 \tabularnewline
V(Y[t],d=1,D=0) & 1.47251987142022 & Range & 5.25 & Trim Var. & 0.984487782805427 \tabularnewline
V(Y[t],d=2,D=0) & 3.88400632183907 & Range & 7.76 & Trim Var. & 2.88805248868777 \tabularnewline
V(Y[t],d=3,D=0) & 11.9586022556391 & Range & 14.01 & Trim Var. & 8.62380141176467 \tabularnewline
V(Y[t],d=0,D=1) & 8.40456578014184 & Range & 11.24 & Trim Var. & 5.99220116144019 \tabularnewline
V(Y[t],d=1,D=1) & 2.31103570767807 & Range & 6.01999999999998 & Trim Var. & 1.49695743902438 \tabularnewline
V(Y[t],d=2,D=1) & 5.46998106280191 & Range & 9.21000000000002 & Trim Var. & 3.53687589743587 \tabularnewline
V(Y[t],d=3,D=1) & 16.4457790909090 & Range & 16.5200000000000 & Trim Var. & 10.1872862348177 \tabularnewline
V(Y[t],d=0,D=2) & 30.9677577777778 & Range & 19.22 & Trim Var. & 23.7409415322581 \tabularnewline
V(Y[t],d=1,D=2) & 6.94435495798318 & Range & 10.4000000000000 & Trim Var. & 4.64649655913978 \tabularnewline
V(Y[t],d=2,D=2) & 15.5646624777183 & Range & 15.2500000000000 & Trim Var. & 10.7377747126436 \tabularnewline
V(Y[t],d=3,D=2) & 45.2286085227271 & Range & 27.2600000000000 & Trim Var. & 30.0520591133004 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=58799&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]2.7035745480226[/C][C]Range[/C][C]7.12[/C][C]Trim Var.[/C][C]1.83315206149546[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]1.47251987142022[/C][C]Range[/C][C]5.25[/C][C]Trim Var.[/C][C]0.984487782805427[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]3.88400632183907[/C][C]Range[/C][C]7.76[/C][C]Trim Var.[/C][C]2.88805248868777[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]11.9586022556391[/C][C]Range[/C][C]14.01[/C][C]Trim Var.[/C][C]8.62380141176467[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]8.40456578014184[/C][C]Range[/C][C]11.24[/C][C]Trim Var.[/C][C]5.99220116144019[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]2.31103570767807[/C][C]Range[/C][C]6.01999999999998[/C][C]Trim Var.[/C][C]1.49695743902438[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]5.46998106280191[/C][C]Range[/C][C]9.21000000000002[/C][C]Trim Var.[/C][C]3.53687589743587[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]16.4457790909090[/C][C]Range[/C][C]16.5200000000000[/C][C]Trim Var.[/C][C]10.1872862348177[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]30.9677577777778[/C][C]Range[/C][C]19.22[/C][C]Trim Var.[/C][C]23.7409415322581[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]6.94435495798318[/C][C]Range[/C][C]10.4000000000000[/C][C]Trim Var.[/C][C]4.64649655913978[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]15.5646624777183[/C][C]Range[/C][C]15.2500000000000[/C][C]Trim Var.[/C][C]10.7377747126436[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]45.2286085227271[/C][C]Range[/C][C]27.2600000000000[/C][C]Trim Var.[/C][C]30.0520591133004[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=58799&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=58799&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)2.7035745480226Range7.12Trim Var.1.83315206149546
V(Y[t],d=1,D=0)1.47251987142022Range5.25Trim Var.0.984487782805427
V(Y[t],d=2,D=0)3.88400632183907Range7.76Trim Var.2.88805248868777
V(Y[t],d=3,D=0)11.9586022556391Range14.01Trim Var.8.62380141176467
V(Y[t],d=0,D=1)8.40456578014184Range11.24Trim Var.5.99220116144019
V(Y[t],d=1,D=1)2.31103570767807Range6.01999999999998Trim Var.1.49695743902438
V(Y[t],d=2,D=1)5.46998106280191Range9.21000000000002Trim Var.3.53687589743587
V(Y[t],d=3,D=1)16.4457790909090Range16.5200000000000Trim Var.10.1872862348177
V(Y[t],d=0,D=2)30.9677577777778Range19.22Trim Var.23.7409415322581
V(Y[t],d=1,D=2)6.94435495798318Range10.4000000000000Trim Var.4.64649655913978
V(Y[t],d=2,D=2)15.5646624777183Range15.2500000000000Trim Var.10.7377747126436
V(Y[t],d=3,D=2)45.2286085227271Range27.2600000000000Trim Var.30.0520591133004


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')