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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 computationFri, 12 Dec 2008 03:51:08 -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/12/t12290791041lupdvewvajia2p.htm/, Retrieved Mon, 13 May 2024 22:19:40 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=32531, Retrieved Mon, 13 May 2024 22:19:40 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact189

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Variance Reduction Matrix] [VRM - vaste rente...] [2008-12-12 10:51:08] [b4fc5040f26b33db57f84cfb8d1d2b82] [Current]
- RM D    [Standard Deviation-Mean Plot] [SDMP inschrijving...] [2008-12-12 11:03:14] [c5a66f1c8528a963efc2b82a8519f117]
- RM        [Variance Reduction Matrix] [VRM - inschrijvin...] [2008-12-12 11:08:27] [c5a66f1c8528a963efc2b82a8519f117]
- RMP         [(Partial) Autocorrelation Function] [ACF - inschrijvin...] [2008-12-12 11:14:36] [c5a66f1c8528a963efc2b82a8519f117]
- RMP           [Spectral Analysis] [SA - inschrijving...] [2008-12-12 11:17:12] [c5a66f1c8528a963efc2b82a8519f117]
-                 [Spectral Analysis] [SA - inschrijving...] [2008-12-12 11:25:51] [c5a66f1c8528a963efc2b82a8519f117]
-  M D            [Spectral Analysis] [spectraalanalyse ...] [2009-12-11 14:10:59] [37a8d600db9abe09a2528d150ccff095]
-  MPD            [Spectral Analysis] [spectraalanalyse ...] [2009-12-11 14:34:45] [37a8d600db9abe09a2528d150ccff095]
-   P           [(Partial) Autocorrelation Function] [SA - inschrijving...] [2008-12-12 11:30:34] [c5a66f1c8528a963efc2b82a8519f117]
-   P           [(Partial) Autocorrelation Function] [ACF - inschrijvin...] [2008-12-12 11:32:48] [c5a66f1c8528a963efc2b82a8519f117]
-                 [(Partial) Autocorrelation Function] [ACF - inschrijvin...] [2008-12-12 11:37:19] [c5a66f1c8528a963efc2b82a8519f117]
- RM                [ARIMA Backward Selection] [ARIMA backward se...] [2008-12-12 11:51:13] [c5a66f1c8528a963efc2b82a8519f117]
- RM                  [ARIMA Forecasting] [ARIMA forecasting...] [2008-12-12 11:57:42] [c5a66f1c8528a963efc2b82a8519f117]
F                       [ARIMA Forecasting] [ARIMA forecasting...] [2008-12-12 12:06:55] [c5a66f1c8528a963efc2b82a8519f117]
-  MPD                    [ARIMA Forecasting] [ARIMA forecasting...] [2009-12-16 20:44:06] [37a8d600db9abe09a2528d150ccff095]
-  MPD                    [ARIMA Forecasting] [Arima forecast - ...] [2009-12-16 20:56:07] [37a8d600db9abe09a2528d150ccff095]
-  MPD                [ARIMA Backward Selection] [Arima backward se...] [2009-12-16 15:42:38] [37a8d600db9abe09a2528d150ccff095]
-  MPD              [(Partial) Autocorrelation Function] [ACF en PACF - uit...] [2009-12-11 15:34:04] [37a8d600db9abe09a2528d150ccff095]
-   P           [(Partial) Autocorrelation Function] [ACF - inschrijvin...] [2008-12-12 14:06:23] [c5a66f1c8528a963efc2b82a8519f117]
-   P             [(Partial) Autocorrelation Function] [ACF - inschrijvin...] [2008-12-12 14:09:53] [c5a66f1c8528a963efc2b82a8519f117]
-   P               [(Partial) Autocorrelation Function] [ACF - inschrijvin...] [2008-12-12 14:13:00] [c5a66f1c8528a963efc2b82a8519f117]
-   P                 [(Partial) Autocorrelation Function] [ACF - inschrijvin...] [2008-12-12 14:23:53] [c5a66f1c8528a963efc2b82a8519f117]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2.21
2.25
2.25
2.45
2.5
2.5
2.64
2.75
2.93
3
3.17
3.25
3.39
3.5
3.5
3.65
3.75
3.75
3.9
4
4
4
4
4
4
4
4
4
4
4
4
4.18
4.25
4.25
3.97
3.42

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=32531&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=32531&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32531&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)0.79233174863388Range2.25Trim Var.0.341219047619048
V(Y[t],d=1,D=0)0.0114202259887006Range0.76Trim Var.0.00187809523809523
V(Y[t],d=2,D=0)0.00823056691992987Range0.49Trim Var.0.00350907111756169
V(Y[t],d=3,D=0)0.0176533877797943Range0.64Trim Var.0.0091921568627451
V(Y[t],d=0,D=1)0.251444302721088Range1.84Trim Var.0.123319088319088
V(Y[t],d=1,D=1)0.0159998226950355Range0.76Trim Var.0.00557537746806039
V(Y[t],d=2,D=1)0.0129057354301573Range0.509999999999999Trim Var.0.00693780487804879
V(Y[t],d=3,D=1)0.0311936714975846Range0.76Trim Var.0.0195532692307692
V(Y[t],d=0,D=2)0.625204354354354Range2.58Trim Var.0.513359090909091
V(Y[t],d=1,D=2)0.0288789682539683Range0.72Trim Var.0.0185161290322581
V(Y[t],d=2,D=2)0.0317820168067227Range0.67Trim Var.0.0222425806451613
V(Y[t],d=3,D=2)0.081716310160428Range1.09Trim Var.0.0582171264367817

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 0.79233174863388 & Range & 2.25 & Trim Var. & 0.341219047619048 \tabularnewline
V(Y[t],d=1,D=0) & 0.0114202259887006 & Range & 0.76 & Trim Var. & 0.00187809523809523 \tabularnewline
V(Y[t],d=2,D=0) & 0.00823056691992987 & Range & 0.49 & Trim Var. & 0.00350907111756169 \tabularnewline
V(Y[t],d=3,D=0) & 0.0176533877797943 & Range & 0.64 & Trim Var. & 0.0091921568627451 \tabularnewline
V(Y[t],d=0,D=1) & 0.251444302721088 & Range & 1.84 & Trim Var. & 0.123319088319088 \tabularnewline
V(Y[t],d=1,D=1) & 0.0159998226950355 & Range & 0.76 & Trim Var. & 0.00557537746806039 \tabularnewline
V(Y[t],d=2,D=1) & 0.0129057354301573 & Range & 0.509999999999999 & Trim Var. & 0.00693780487804879 \tabularnewline
V(Y[t],d=3,D=1) & 0.0311936714975846 & Range & 0.76 & Trim Var. & 0.0195532692307692 \tabularnewline
V(Y[t],d=0,D=2) & 0.625204354354354 & Range & 2.58 & Trim Var. & 0.513359090909091 \tabularnewline
V(Y[t],d=1,D=2) & 0.0288789682539683 & Range & 0.72 & Trim Var. & 0.0185161290322581 \tabularnewline
V(Y[t],d=2,D=2) & 0.0317820168067227 & Range & 0.67 & Trim Var. & 0.0222425806451613 \tabularnewline
V(Y[t],d=3,D=2) & 0.081716310160428 & Range & 1.09 & Trim Var. & 0.0582171264367817 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32531&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]0.79233174863388[/C][C]Range[/C][C]2.25[/C][C]Trim Var.[/C][C]0.341219047619048[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]0.0114202259887006[/C][C]Range[/C][C]0.76[/C][C]Trim Var.[/C][C]0.00187809523809523[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]0.00823056691992987[/C][C]Range[/C][C]0.49[/C][C]Trim Var.[/C][C]0.00350907111756169[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]0.0176533877797943[/C][C]Range[/C][C]0.64[/C][C]Trim Var.[/C][C]0.0091921568627451[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]0.251444302721088[/C][C]Range[/C][C]1.84[/C][C]Trim Var.[/C][C]0.123319088319088[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]0.0159998226950355[/C][C]Range[/C][C]0.76[/C][C]Trim Var.[/C][C]0.00557537746806039[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]0.0129057354301573[/C][C]Range[/C][C]0.509999999999999[/C][C]Trim Var.[/C][C]0.00693780487804879[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]0.0311936714975846[/C][C]Range[/C][C]0.76[/C][C]Trim Var.[/C][C]0.0195532692307692[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]0.625204354354354[/C][C]Range[/C][C]2.58[/C][C]Trim Var.[/C][C]0.513359090909091[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]0.0288789682539683[/C][C]Range[/C][C]0.72[/C][C]Trim Var.[/C][C]0.0185161290322581[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]0.0317820168067227[/C][C]Range[/C][C]0.67[/C][C]Trim Var.[/C][C]0.0222425806451613[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]0.081716310160428[/C][C]Range[/C][C]1.09[/C][C]Trim Var.[/C][C]0.0582171264367817[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32531&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32531&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)0.79233174863388Range2.25Trim Var.0.341219047619048
V(Y[t],d=1,D=0)0.0114202259887006Range0.76Trim Var.0.00187809523809523
V(Y[t],d=2,D=0)0.00823056691992987Range0.49Trim Var.0.00350907111756169
V(Y[t],d=3,D=0)0.0176533877797943Range0.64Trim Var.0.0091921568627451
V(Y[t],d=0,D=1)0.251444302721088Range1.84Trim Var.0.123319088319088
V(Y[t],d=1,D=1)0.0159998226950355Range0.76Trim Var.0.00557537746806039
V(Y[t],d=2,D=1)0.0129057354301573Range0.509999999999999Trim Var.0.00693780487804879
V(Y[t],d=3,D=1)0.0311936714975846Range0.76Trim Var.0.0195532692307692
V(Y[t],d=0,D=2)0.625204354354354Range2.58Trim Var.0.513359090909091
V(Y[t],d=1,D=2)0.0288789682539683Range0.72Trim Var.0.0185161290322581
V(Y[t],d=2,D=2)0.0317820168067227Range0.67Trim Var.0.0222425806451613
V(Y[t],d=3,D=2)0.081716310160428Range1.09Trim Var.0.0582171264367817


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')