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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 computationTue, 09 Dec 2008 09:07:08 -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/09/t1228838871kioczlbfvz1u36b.htm/, Retrieved Tue, 14 May 2024 12:35:39 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=31550, Retrieved Tue, 14 May 2024 12:35:39 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact201

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Mean Plot] [Gilliam Schoorel] [2008-11-06 14:07:56] [666bda00bbd072dde5655a1423b1377b]
- RM D    [Variance Reduction Matrix] [VRM suiker] [2008-12-09 16:07:08] [3fc0b50a130253095e963177b0139835] [Current]
-    D      [Variance Reduction Matrix] [VRM chocpasta zon...] [2008-12-18 11:26:21] [f77c9ab3b413812d7baee6b7ec69a15d]
-  M D        [Variance Reduction Matrix] [Variance Reductio...] [2010-12-06 13:25:13] [ff7c1e95cf99a1dae07ec89975494dde]
- RMPD      [(Partial) Autocorrelation Function] [ACF chocopasta zo...] [2008-12-18 11:31:51] [f77c9ab3b413812d7baee6b7ec69a15d]
-   P         [(Partial) Autocorrelation Function] [ACF chocopasta me...] [2008-12-18 11:38:58] [f77c9ab3b413812d7baee6b7ec69a15d]
-  MPD          [(Partial) Autocorrelation Function] [autocorrelatie na...] [2010-12-06 13:29:52] [ff7c1e95cf99a1dae07ec89975494dde]
- RMP         [Spectral Analysis] [spectraalanalyse ...] [2008-12-18 11:44:43] [f77c9ab3b413812d7baee6b7ec69a15d]
-  M D          [Spectral Analysis] [Spectrale analyse...] [2010-12-06 13:31:40] [ff7c1e95cf99a1dae07ec89975494dde]
- RMP         [Spectral Analysis] [Spectraalanalyse ...] [2008-12-18 11:49:50] [f77c9ab3b413812d7baee6b7ec69a15d]
-  M D          [Spectral Analysis] [spectraalanalyse ...] [2010-12-06 13:33:54] [ff7c1e95cf99a1dae07ec89975494dde]
-   P             [Spectral Analysis] [Spectral analyse ...] [2010-12-19 11:19:30] [ff7c1e95cf99a1dae07ec89975494dde]
- RMP         [Standard Deviation-Mean Plot] [lamda suiker] [2008-12-18 11:59:17] [f77c9ab3b413812d7baee6b7ec69a15d]
- RMP         [Standard Deviation-Mean Plot] [Lambda chocopasta] [2008-12-18 11:59:17] [f77c9ab3b413812d7baee6b7ec69a15d]
-  M D          [Standard Deviation-Mean Plot] [Box cox transform...] [2010-12-07 10:11:36] [ff7c1e95cf99a1dae07ec89975494dde]
- RMPD        [Standard Deviation-Mean Plot] [lambda suiker] [2008-12-18 12:10:37] [f77c9ab3b413812d7baee6b7ec69a15d]
-  M D          [Standard Deviation-Mean Plot] [Box cox transform...] [2010-12-07 10:09:06] [ff7c1e95cf99a1dae07ec89975494dde]
-  MPD        [(Partial) Autocorrelation Function] [Autocorrelatie gr...] [2010-12-06 13:28:06] [ff7c1e95cf99a1dae07ec89975494dde]
-  M D      [Variance Reduction Matrix] [Variance Reductio...] [2010-12-06 13:10:45] [ff7c1e95cf99a1dae07ec89975494dde]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
101,02
100,67
100,47
100,38
100,33
100,34
100,37
100,39
100,21
100,21
100,22
100,28
100,25
100,25
100,21
100,16
100,18
100,1
99,96
99,88
99,88
99,86
99,84
99,8
99,82
99,81
99,92
100,03
99,99
100,02
100,01
100,13
100,33
100,13
99,96
100,05
99,83
99,8
100,01
100,1
100,13
100,16
100,41
101,34
101,65
101,85
102,07
102,12
102,14
102,21
102,28
102,19
102,33
102,54
102,44
102,78
102,9
103,08
102,77
102,65
102,71
103,29
102,86
103,45
103,72
103,65
103,83
104,45
105,14
105,07
105,31
105,19
105,3
105,02
105,17
105,28
105,45
105,38
105,8
105,96
105,08
105,11
105,61
105,5

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'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31550&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31550&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31550&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'George Udny Yule' @ 72.249.76.132






Variance Reduction Matrix
V(Y[t],d=0,D=0)4.27624662937464Range6.16Trim Var.3.57431375416513
V(Y[t],d=1,D=0)0.0618193652659423Range1.81000000000000Trim Var.0.0207473363774736
V(Y[t],d=2,D=0)0.113729599518219Range2.06000000000000Trim Var.0.0412612676056348
V(Y[t],d=3,D=0)0.323923364197538Range3.56000000000007Trim Var.0.113031388329983
V(Y[t],d=0,D=1)1.03594223395931Range3.36Trim Var.0.863515252976191
V(Y[t],d=1,D=1)0.123065311871229Range2.38000000000001Trim Var.0.0476587301587312
V(Y[t],d=2,D=1)0.247642732919261Range2.77999999999999Trim Var.0.0977252247488129
V(Y[t],d=3,D=1)0.75976687979542Range5.28000000000003Trim Var.0.287124316939901
V(Y[t],d=0,D=2)1.55897115819209Range4.72Trim Var.1.1301784765898
V(Y[t],d=1,D=2)0.336430216247813Range3.22000000000001Trim Var.0.155956095791004
V(Y[t],d=2,D=2)0.673770871143395Range4.73000000000003Trim Var.0.305732880844656
V(Y[t],d=3,D=2)2.14238314536348Range8.58000000000007Trim Var.0.867726352941212

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 4.27624662937464 & Range & 6.16 & Trim Var. & 3.57431375416513 \tabularnewline
V(Y[t],d=1,D=0) & 0.0618193652659423 & Range & 1.81000000000000 & Trim Var. & 0.0207473363774736 \tabularnewline
V(Y[t],d=2,D=0) & 0.113729599518219 & Range & 2.06000000000000 & Trim Var. & 0.0412612676056348 \tabularnewline
V(Y[t],d=3,D=0) & 0.323923364197538 & Range & 3.56000000000007 & Trim Var. & 0.113031388329983 \tabularnewline
V(Y[t],d=0,D=1) & 1.03594223395931 & Range & 3.36 & Trim Var. & 0.863515252976191 \tabularnewline
V(Y[t],d=1,D=1) & 0.123065311871229 & Range & 2.38000000000001 & Trim Var. & 0.0476587301587312 \tabularnewline
V(Y[t],d=2,D=1) & 0.247642732919261 & Range & 2.77999999999999 & Trim Var. & 0.0977252247488129 \tabularnewline
V(Y[t],d=3,D=1) & 0.75976687979542 & Range & 5.28000000000003 & Trim Var. & 0.287124316939901 \tabularnewline
V(Y[t],d=0,D=2) & 1.55897115819209 & Range & 4.72 & Trim Var. & 1.1301784765898 \tabularnewline
V(Y[t],d=1,D=2) & 0.336430216247813 & Range & 3.22000000000001 & Trim Var. & 0.155956095791004 \tabularnewline
V(Y[t],d=2,D=2) & 0.673770871143395 & Range & 4.73000000000003 & Trim Var. & 0.305732880844656 \tabularnewline
V(Y[t],d=3,D=2) & 2.14238314536348 & Range & 8.58000000000007 & Trim Var. & 0.867726352941212 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31550&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]4.27624662937464[/C][C]Range[/C][C]6.16[/C][C]Trim Var.[/C][C]3.57431375416513[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]0.0618193652659423[/C][C]Range[/C][C]1.81000000000000[/C][C]Trim Var.[/C][C]0.0207473363774736[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]0.113729599518219[/C][C]Range[/C][C]2.06000000000000[/C][C]Trim Var.[/C][C]0.0412612676056348[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]0.323923364197538[/C][C]Range[/C][C]3.56000000000007[/C][C]Trim Var.[/C][C]0.113031388329983[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]1.03594223395931[/C][C]Range[/C][C]3.36[/C][C]Trim Var.[/C][C]0.863515252976191[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]0.123065311871229[/C][C]Range[/C][C]2.38000000000001[/C][C]Trim Var.[/C][C]0.0476587301587312[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]0.247642732919261[/C][C]Range[/C][C]2.77999999999999[/C][C]Trim Var.[/C][C]0.0977252247488129[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]0.75976687979542[/C][C]Range[/C][C]5.28000000000003[/C][C]Trim Var.[/C][C]0.287124316939901[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]1.55897115819209[/C][C]Range[/C][C]4.72[/C][C]Trim Var.[/C][C]1.1301784765898[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]0.336430216247813[/C][C]Range[/C][C]3.22000000000001[/C][C]Trim Var.[/C][C]0.155956095791004[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]0.673770871143395[/C][C]Range[/C][C]4.73000000000003[/C][C]Trim Var.[/C][C]0.305732880844656[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]2.14238314536348[/C][C]Range[/C][C]8.58000000000007[/C][C]Trim Var.[/C][C]0.867726352941212[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31550&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31550&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)4.27624662937464Range6.16Trim Var.3.57431375416513
V(Y[t],d=1,D=0)0.0618193652659423Range1.81000000000000Trim Var.0.0207473363774736
V(Y[t],d=2,D=0)0.113729599518219Range2.06000000000000Trim Var.0.0412612676056348
V(Y[t],d=3,D=0)0.323923364197538Range3.56000000000007Trim Var.0.113031388329983
V(Y[t],d=0,D=1)1.03594223395931Range3.36Trim Var.0.863515252976191
V(Y[t],d=1,D=1)0.123065311871229Range2.38000000000001Trim Var.0.0476587301587312
V(Y[t],d=2,D=1)0.247642732919261Range2.77999999999999Trim Var.0.0977252247488129
V(Y[t],d=3,D=1)0.75976687979542Range5.28000000000003Trim Var.0.287124316939901
V(Y[t],d=0,D=2)1.55897115819209Range4.72Trim Var.1.1301784765898
V(Y[t],d=1,D=2)0.336430216247813Range3.22000000000001Trim Var.0.155956095791004
V(Y[t],d=2,D=2)0.673770871143395Range4.73000000000003Trim Var.0.305732880844656
V(Y[t],d=3,D=2)2.14238314536348Range8.58000000000007Trim Var.0.867726352941212


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')