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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 computationSat, 28 Nov 2009 11:32:32 -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/28/t1259433229ij3g0sbfi77ne4q.htm/, Retrieved Fri, 03 May 2024 13:05:03 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=61520, Retrieved Fri, 03 May 2024 13:05:03 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact190

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] [Workshop] [2009-11-28 18:32:32] [aef022288383377281176d9807aba5bf] [Current]
-   PD    [Variance Reduction Matrix] [] [2009-12-04 13:07:51] [0750c128064677e728c9436fc3f45ae7]
-   PD    [Variance Reduction Matrix] [Oplossing VRM ] [2009-12-04 16:00:35] [4395c69e961f9a13a0559fd2f0a72538]
Feedback Forum
2009-12-04 13:10:02 [Angelo Stuer] [reply] 
zorg dat je niet vergeet om de seasonal period op 12 in te stellen. Hierdoor kom je andere varianties uit en is er slechts 1 kleinste variantie, nl. bij d=0
http://www.freestatistics.org/blog/index.php?v=date/2009/Dec/04/t12599321226qxbfwk9wmnwry6.htm/

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
102,86
102,55
102,28
102,26
102,57
103,08
102,76
102,51
102,87
103,14
103,12
103,16
102,48
102,57
102,88
102,63
102,38
101,69
101,96
102,19
101,87
101,6
101,63
101,22
101,21
101,49
101,64
101,66
101,77
101,82
101,78
101,28
101,29
101,37
101,12
101,51
102,24
102,94
103,09
103,46
103,64
104,39
104,15
105,21
105,8
105,91
105,39
105,46
104,72
103,14
102,63
102,32
101,93
100,62
100,6
99,63
98,9
98,32
99,22
98,81

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=61520&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=61520&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61520&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)2.53353152542373Range7.59Trim Var.1.40767044025157
V(Y[t],d=1,D=0)0.249905026300408Range2.63999999999999Trim Var.0.133929245283018
V(Y[t],d=2,D=0)0.359533817301873Range2.79000000000002Trim Var.0.222237707390646
V(Y[t],d=3,D=0)1.01449511278195Range5.08Trim Var.0.542294588235289
V(Y[t],d=0,D=1)0.249905026300408Range2.63999999999999Trim Var.0.133929245283018
V(Y[t],d=1,D=1)0.359533817301873Range2.79000000000002Trim Var.0.222237707390646
V(Y[t],d=2,D=1)1.01449511278195Range5.08Trim Var.0.542294588235289
V(Y[t],d=3,D=1)3.12011792207790Range8.29999999999995Trim Var.1.68585714285712
V(Y[t],d=0,D=2)0.359533817301873Range2.79000000000002Trim Var.0.222237707390646
V(Y[t],d=1,D=2)1.01449511278195Range5.08Trim Var.0.542294588235289
V(Y[t],d=2,D=2)3.12011792207790Range8.29999999999995Trim Var.1.68585714285712
V(Y[t],d=3,D=2)10.3916415488215Range15.7899999999999Trim Var.5.78583086734688

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 2.53353152542373 & Range & 7.59 & Trim Var. & 1.40767044025157 \tabularnewline
V(Y[t],d=1,D=0) & 0.249905026300408 & Range & 2.63999999999999 & Trim Var. & 0.133929245283018 \tabularnewline
V(Y[t],d=2,D=0) & 0.359533817301873 & Range & 2.79000000000002 & Trim Var. & 0.222237707390646 \tabularnewline
V(Y[t],d=3,D=0) & 1.01449511278195 & Range & 5.08 & Trim Var. & 0.542294588235289 \tabularnewline
V(Y[t],d=0,D=1) & 0.249905026300408 & Range & 2.63999999999999 & Trim Var. & 0.133929245283018 \tabularnewline
V(Y[t],d=1,D=1) & 0.359533817301873 & Range & 2.79000000000002 & Trim Var. & 0.222237707390646 \tabularnewline
V(Y[t],d=2,D=1) & 1.01449511278195 & Range & 5.08 & Trim Var. & 0.542294588235289 \tabularnewline
V(Y[t],d=3,D=1) & 3.12011792207790 & Range & 8.29999999999995 & Trim Var. & 1.68585714285712 \tabularnewline
V(Y[t],d=0,D=2) & 0.359533817301873 & Range & 2.79000000000002 & Trim Var. & 0.222237707390646 \tabularnewline
V(Y[t],d=1,D=2) & 1.01449511278195 & Range & 5.08 & Trim Var. & 0.542294588235289 \tabularnewline
V(Y[t],d=2,D=2) & 3.12011792207790 & Range & 8.29999999999995 & Trim Var. & 1.68585714285712 \tabularnewline
V(Y[t],d=3,D=2) & 10.3916415488215 & Range & 15.7899999999999 & Trim Var. & 5.78583086734688 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=61520&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]2.53353152542373[/C][C]Range[/C][C]7.59[/C][C]Trim Var.[/C][C]1.40767044025157[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]0.249905026300408[/C][C]Range[/C][C]2.63999999999999[/C][C]Trim Var.[/C][C]0.133929245283018[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]0.359533817301873[/C][C]Range[/C][C]2.79000000000002[/C][C]Trim Var.[/C][C]0.222237707390646[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]1.01449511278195[/C][C]Range[/C][C]5.08[/C][C]Trim Var.[/C][C]0.542294588235289[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]0.249905026300408[/C][C]Range[/C][C]2.63999999999999[/C][C]Trim Var.[/C][C]0.133929245283018[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]0.359533817301873[/C][C]Range[/C][C]2.79000000000002[/C][C]Trim Var.[/C][C]0.222237707390646[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]1.01449511278195[/C][C]Range[/C][C]5.08[/C][C]Trim Var.[/C][C]0.542294588235289[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]3.12011792207790[/C][C]Range[/C][C]8.29999999999995[/C][C]Trim Var.[/C][C]1.68585714285712[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]0.359533817301873[/C][C]Range[/C][C]2.79000000000002[/C][C]Trim Var.[/C][C]0.222237707390646[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]1.01449511278195[/C][C]Range[/C][C]5.08[/C][C]Trim Var.[/C][C]0.542294588235289[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]3.12011792207790[/C][C]Range[/C][C]8.29999999999995[/C][C]Trim Var.[/C][C]1.68585714285712[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]10.3916415488215[/C][C]Range[/C][C]15.7899999999999[/C][C]Trim Var.[/C][C]5.78583086734688[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=61520&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=61520&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)2.53353152542373Range7.59Trim Var.1.40767044025157
V(Y[t],d=1,D=0)0.249905026300408Range2.63999999999999Trim Var.0.133929245283018
V(Y[t],d=2,D=0)0.359533817301873Range2.79000000000002Trim Var.0.222237707390646
V(Y[t],d=3,D=0)1.01449511278195Range5.08Trim Var.0.542294588235289
V(Y[t],d=0,D=1)0.249905026300408Range2.63999999999999Trim Var.0.133929245283018
V(Y[t],d=1,D=1)0.359533817301873Range2.79000000000002Trim Var.0.222237707390646
V(Y[t],d=2,D=1)1.01449511278195Range5.08Trim Var.0.542294588235289
V(Y[t],d=3,D=1)3.12011792207790Range8.29999999999995Trim Var.1.68585714285712
V(Y[t],d=0,D=2)0.359533817301873Range2.79000000000002Trim Var.0.222237707390646
V(Y[t],d=1,D=2)1.01449511278195Range5.08Trim Var.0.542294588235289
V(Y[t],d=2,D=2)3.12011792207790Range8.29999999999995Trim Var.1.68585714285712
V(Y[t],d=3,D=2)10.3916415488215Range15.7899999999999Trim Var.5.78583086734688


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')