FreeStatistics.org

Free Statistics

of Irreproducible Research!

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 computationSat, 05 Dec 2009 05:37:10 -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/05/t1260016800yzq9yg9rx5v10iy.htm/, Retrieved Mon, 29 Apr 2024 06:12:45 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=64240, Retrieved Mon, 29 Apr 2024 06:12:45 +0000
QR Codes:

Original text written by user:WS 9 Estimation of Box-Jenkins ARIMA models
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact163

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       [Standard Deviation-Mean Plot] [Identifying Integ...] [2009-11-22 12:50:05] [b98453cac15ba1066b407e146608df68]
-    D        [Standard Deviation-Mean Plot] [standard deviatio...] [2009-11-24 21:20:13] [8b1aef4e7013bd33fbc2a5833375c5f5]
F    D          [Standard Deviation-Mean Plot] [WS8(8)] [2009-11-27 11:40:10] [7d268329e554b8694908ba13e6e6f258]
- RMPD              [Variance Reduction Matrix] [WS 9 Estimation o...] [2009-12-05 12:37:10] [9b6f46453e60f88d91cef176fe926003] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
10.9
10
9.2
9.2
9.5
9.6
9.5
9.1
8.9
9
10.1
10.3
10.2
9.6
9.2
9.3
9.4
9.4
9.2
9
9
9
9.8
10
9.8
9.3
9
9
9.1
9.1
9.1
9.2
8.8
8.3
8.4
8.1
7.7
7.9
7.9
8
7.9
7.6
7.1
6.8
6.5
6.9
8.2
8.7
8.3
7.9
7.5
7.8
8.3
8.4
8.2
7.7
7.2
7.3
8.1
8.5

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'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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64240&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64240&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64240&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'Gwilym Jenkins' @ 72.249.127.135






Variance Reduction Matrix
V(Y[t],d=0,D=0)0.904745762711864Range4.4Trim Var.0.60440251572327
V(Y[t],d=1,D=0)0.175213325540619Range2.2Trim Var.0.0904716981132076
V(Y[t],d=2,D=0)0.191944948578342Range1.9Trim Var.0.112337254901961
V(Y[t],d=3,D=0)0.363671679197995Range2.80000000000000Trim Var.0.187083333333333
V(Y[t],d=0,D=1)0.175213325540619Range2.2Trim Var.0.0904716981132076
V(Y[t],d=1,D=1)0.191944948578342Range1.9Trim Var.0.112337254901961
V(Y[t],d=2,D=1)0.363671679197995Range2.80000000000000Trim Var.0.187083333333333
V(Y[t],d=3,D=1)0.930948051948051Range5.09999999999999Trim Var.0.503412244897959
V(Y[t],d=0,D=2)0.191944948578342Range1.9Trim Var.0.112337254901961
V(Y[t],d=1,D=2)0.363671679197995Range2.80000000000000Trim Var.0.187083333333333
V(Y[t],d=2,D=2)0.930948051948051Range5.09999999999999Trim Var.0.503412244897959
V(Y[t],d=3,D=2)2.85925925925926Range8.39999999999998Trim Var.1.46210884353741

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 0.904745762711864 & Range & 4.4 & Trim Var. & 0.60440251572327 \tabularnewline
V(Y[t],d=1,D=0) & 0.175213325540619 & Range & 2.2 & Trim Var. & 0.0904716981132076 \tabularnewline
V(Y[t],d=2,D=0) & 0.191944948578342 & Range & 1.9 & Trim Var. & 0.112337254901961 \tabularnewline
V(Y[t],d=3,D=0) & 0.363671679197995 & Range & 2.80000000000000 & Trim Var. & 0.187083333333333 \tabularnewline
V(Y[t],d=0,D=1) & 0.175213325540619 & Range & 2.2 & Trim Var. & 0.0904716981132076 \tabularnewline
V(Y[t],d=1,D=1) & 0.191944948578342 & Range & 1.9 & Trim Var. & 0.112337254901961 \tabularnewline
V(Y[t],d=2,D=1) & 0.363671679197995 & Range & 2.80000000000000 & Trim Var. & 0.187083333333333 \tabularnewline
V(Y[t],d=3,D=1) & 0.930948051948051 & Range & 5.09999999999999 & Trim Var. & 0.503412244897959 \tabularnewline
V(Y[t],d=0,D=2) & 0.191944948578342 & Range & 1.9 & Trim Var. & 0.112337254901961 \tabularnewline
V(Y[t],d=1,D=2) & 0.363671679197995 & Range & 2.80000000000000 & Trim Var. & 0.187083333333333 \tabularnewline
V(Y[t],d=2,D=2) & 0.930948051948051 & Range & 5.09999999999999 & Trim Var. & 0.503412244897959 \tabularnewline
V(Y[t],d=3,D=2) & 2.85925925925926 & Range & 8.39999999999998 & Trim Var. & 1.46210884353741 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=64240&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]0.904745762711864[/C][C]Range[/C][C]4.4[/C][C]Trim Var.[/C][C]0.60440251572327[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]0.175213325540619[/C][C]Range[/C][C]2.2[/C][C]Trim Var.[/C][C]0.0904716981132076[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]0.191944948578342[/C][C]Range[/C][C]1.9[/C][C]Trim Var.[/C][C]0.112337254901961[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]0.363671679197995[/C][C]Range[/C][C]2.80000000000000[/C][C]Trim Var.[/C][C]0.187083333333333[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]0.175213325540619[/C][C]Range[/C][C]2.2[/C][C]Trim Var.[/C][C]0.0904716981132076[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]0.191944948578342[/C][C]Range[/C][C]1.9[/C][C]Trim Var.[/C][C]0.112337254901961[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]0.363671679197995[/C][C]Range[/C][C]2.80000000000000[/C][C]Trim Var.[/C][C]0.187083333333333[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]0.930948051948051[/C][C]Range[/C][C]5.09999999999999[/C][C]Trim Var.[/C][C]0.503412244897959[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]0.191944948578342[/C][C]Range[/C][C]1.9[/C][C]Trim Var.[/C][C]0.112337254901961[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]0.363671679197995[/C][C]Range[/C][C]2.80000000000000[/C][C]Trim Var.[/C][C]0.187083333333333[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]0.930948051948051[/C][C]Range[/C][C]5.09999999999999[/C][C]Trim Var.[/C][C]0.503412244897959[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]2.85925925925926[/C][C]Range[/C][C]8.39999999999998[/C][C]Trim Var.[/C][C]1.46210884353741[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=64240&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=64240&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)0.904745762711864Range4.4Trim Var.0.60440251572327
V(Y[t],d=1,D=0)0.175213325540619Range2.2Trim Var.0.0904716981132076
V(Y[t],d=2,D=0)0.191944948578342Range1.9Trim Var.0.112337254901961
V(Y[t],d=3,D=0)0.363671679197995Range2.80000000000000Trim Var.0.187083333333333
V(Y[t],d=0,D=1)0.175213325540619Range2.2Trim Var.0.0904716981132076
V(Y[t],d=1,D=1)0.191944948578342Range1.9Trim Var.0.112337254901961
V(Y[t],d=2,D=1)0.363671679197995Range2.80000000000000Trim Var.0.187083333333333
V(Y[t],d=3,D=1)0.930948051948051Range5.09999999999999Trim Var.0.503412244897959
V(Y[t],d=0,D=2)0.191944948578342Range1.9Trim Var.0.112337254901961
V(Y[t],d=1,D=2)0.363671679197995Range2.80000000000000Trim Var.0.187083333333333
V(Y[t],d=2,D=2)0.930948051948051Range5.09999999999999Trim Var.0.503412244897959
V(Y[t],d=3,D=2)2.85925925925926Range8.39999999999998Trim Var.1.46210884353741


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')