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 computationTue, 02 Dec 2008 17:06:06 -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/03/t1228262913urzu2ut1hpjwnkq.htm/, Retrieved Fri, 17 May 2024 18:12:01 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=28541, Retrieved Fri, 17 May 2024 18:12:01 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsQ8 non stationary time series
Estimated Impact242

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [Variance Reduction Matrix] [Q8 non stationary...] [2008-12-03 00:06:06] [9f72e095d5529918bf5b0810c01bf6ce] [Current]
Feedback Forum
2008-12-06 17:58:28 [a2386b643d711541400692649981f2dc] [reply] 
Je antwoord is niet fout maar te kort! Je vergat de andere methodes ook te berekenen om na te gana of de bevindingen van de VRM wel kloppen.
2008-12-09 00:25:44 [Jessica Alves Pires] [reply] 
Ik ga hiermee akkoord.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1.0622
1.0773
1.0807
1.0848
1.1582
1.1663
1.1372
1.1139
1.1222
1.1692
1.1702
1.2286
1.2613
1.2646
1.2262
1.1985
1.2007
1.2138
1.2266
1.2176
1.2218
1.249
1.2991
1.3408
1.3119
1.3014
1.3201
1.2938
1.2694
1.2165
1.2037
1.2292
1.2256
1.2015
1.1786
1.1856
1.2103
1.1938
1.202
1.2271
1.277
1.265
1.2684
1.2811
1.2727
1.2611
1.2881
1.3213
1.2999
1.3074
1.3242
1.3516
1.3511
1.3419
1.3716
1.3622
1.3896
1.4227
1.4684
1.457

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=28541&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=28541&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28541&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)0.00799657938983051Range0.4062Trim Var.0.00485724085604472
V(Y[t],d=1,D=0)0.000678424926943307Range0.1263Trim Var.0.000451279484760521
V(Y[t],d=2,D=0)0.00107565933756805Range0.1399Trim Var.0.000755666285822017
V(Y[t],d=3,D=0)0.00263028605889723Range0.238Trim Var.0.00177869279999999
V(Y[t],d=0,D=1)0.00700521546099291Range0.3543Trim Var.0.00409275684668990
V(Y[t],d=1,D=1)0.0014154582053654Range0.147300000000000Trim Var.0.000968817719512193
V(Y[t],d=2,D=1)0.00207558649275361Range0.1606Trim Var.0.00156716061538461
V(Y[t],d=3,D=1)0.00464189290909087Range0.290299999999999Trim Var.0.0027178318353576
V(Y[t],d=0,D=2)0.0205540802777778Range0.5583Trim Var.0.0143013074092742
V(Y[t],d=1,D=2)0.00431925369747898Range0.247599999999999Trim Var.0.00292845279569892
V(Y[t],d=2,D=2)0.00619850185383242Range0.2938Trim Var.0.0045126570689655
V(Y[t],d=3,D=2)0.0134184487689393Range0.530899999999999Trim Var.0.00787568492610831

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 0.00799657938983051 & Range & 0.4062 & Trim Var. & 0.00485724085604472 \tabularnewline
V(Y[t],d=1,D=0) & 0.000678424926943307 & Range & 0.1263 & Trim Var. & 0.000451279484760521 \tabularnewline
V(Y[t],d=2,D=0) & 0.00107565933756805 & Range & 0.1399 & Trim Var. & 0.000755666285822017 \tabularnewline
V(Y[t],d=3,D=0) & 0.00263028605889723 & Range & 0.238 & Trim Var. & 0.00177869279999999 \tabularnewline
V(Y[t],d=0,D=1) & 0.00700521546099291 & Range & 0.3543 & Trim Var. & 0.00409275684668990 \tabularnewline
V(Y[t],d=1,D=1) & 0.0014154582053654 & Range & 0.147300000000000 & Trim Var. & 0.000968817719512193 \tabularnewline
V(Y[t],d=2,D=1) & 0.00207558649275361 & Range & 0.1606 & Trim Var. & 0.00156716061538461 \tabularnewline
V(Y[t],d=3,D=1) & 0.00464189290909087 & Range & 0.290299999999999 & Trim Var. & 0.0027178318353576 \tabularnewline
V(Y[t],d=0,D=2) & 0.0205540802777778 & Range & 0.5583 & Trim Var. & 0.0143013074092742 \tabularnewline
V(Y[t],d=1,D=2) & 0.00431925369747898 & Range & 0.247599999999999 & Trim Var. & 0.00292845279569892 \tabularnewline
V(Y[t],d=2,D=2) & 0.00619850185383242 & Range & 0.2938 & Trim Var. & 0.0045126570689655 \tabularnewline
V(Y[t],d=3,D=2) & 0.0134184487689393 & Range & 0.530899999999999 & Trim Var. & 0.00787568492610831 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28541&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]0.00799657938983051[/C][C]Range[/C][C]0.4062[/C][C]Trim Var.[/C][C]0.00485724085604472[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]0.000678424926943307[/C][C]Range[/C][C]0.1263[/C][C]Trim Var.[/C][C]0.000451279484760521[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]0.00107565933756805[/C][C]Range[/C][C]0.1399[/C][C]Trim Var.[/C][C]0.000755666285822017[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]0.00263028605889723[/C][C]Range[/C][C]0.238[/C][C]Trim Var.[/C][C]0.00177869279999999[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]0.00700521546099291[/C][C]Range[/C][C]0.3543[/C][C]Trim Var.[/C][C]0.00409275684668990[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]0.0014154582053654[/C][C]Range[/C][C]0.147300000000000[/C][C]Trim Var.[/C][C]0.000968817719512193[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]0.00207558649275361[/C][C]Range[/C][C]0.1606[/C][C]Trim Var.[/C][C]0.00156716061538461[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]0.00464189290909087[/C][C]Range[/C][C]0.290299999999999[/C][C]Trim Var.[/C][C]0.0027178318353576[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]0.0205540802777778[/C][C]Range[/C][C]0.5583[/C][C]Trim Var.[/C][C]0.0143013074092742[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]0.00431925369747898[/C][C]Range[/C][C]0.247599999999999[/C][C]Trim Var.[/C][C]0.00292845279569892[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]0.00619850185383242[/C][C]Range[/C][C]0.2938[/C][C]Trim Var.[/C][C]0.0045126570689655[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]0.0134184487689393[/C][C]Range[/C][C]0.530899999999999[/C][C]Trim Var.[/C][C]0.00787568492610831[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28541&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28541&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)0.00799657938983051Range0.4062Trim Var.0.00485724085604472
V(Y[t],d=1,D=0)0.000678424926943307Range0.1263Trim Var.0.000451279484760521
V(Y[t],d=2,D=0)0.00107565933756805Range0.1399Trim Var.0.000755666285822017
V(Y[t],d=3,D=0)0.00263028605889723Range0.238Trim Var.0.00177869279999999
V(Y[t],d=0,D=1)0.00700521546099291Range0.3543Trim Var.0.00409275684668990
V(Y[t],d=1,D=1)0.0014154582053654Range0.147300000000000Trim Var.0.000968817719512193
V(Y[t],d=2,D=1)0.00207558649275361Range0.1606Trim Var.0.00156716061538461
V(Y[t],d=3,D=1)0.00464189290909087Range0.290299999999999Trim Var.0.0027178318353576
V(Y[t],d=0,D=2)0.0205540802777778Range0.5583Trim Var.0.0143013074092742
V(Y[t],d=1,D=2)0.00431925369747898Range0.247599999999999Trim Var.0.00292845279569892
V(Y[t],d=2,D=2)0.00619850185383242Range0.2938Trim Var.0.0045126570689655
V(Y[t],d=3,D=2)0.0134184487689393Range0.530899999999999Trim Var.0.00787568492610831


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')