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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 computationMon, 01 Dec 2008 03:54:28 -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/01/t1228128922bix6b7o6d4s7d9v.htm/, Retrieved Sun, 05 May 2024 13:02:04 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=26867, Retrieved Sun, 05 May 2024 13:02:04 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact208

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Law of Averages] [Random Walk Simul...] [2008-11-25 18:31:28] [b98453cac15ba1066b407e146608df68]
- RMPD  [Standard Deviation-Mean Plot] [Q5: Standard Devi...] [2008-11-30 15:50:04] [44ec60eb6065a3f81a5f756bd5af1faf]
- RM D      [Variance Reduction Matrix] [VRM: Werkloosheid...] [2008-12-01 10:54:28] [924502d03698cd41cacbcd1327858815] [Current]
- RMP         [Spectral Analysis] [Spectraal analyse...] [2008-12-08 18:58:46] [44ec60eb6065a3f81a5f756bd5af1faf]
- RMP         [Spectral Analysis] [Spectraal analyse...] [2008-12-08 19:02:27] [44ec60eb6065a3f81a5f756bd5af1faf]
- RMP           [(Partial) Autocorrelation Function] [ACF - Werklooshei...] [2008-12-08 19:18:55] [44ec60eb6065a3f81a5f756bd5af1faf]
- RMP           [ARIMA Backward Selection] [Backward Selectio...] [2008-12-08 19:30:50] [44ec60eb6065a3f81a5f756bd5af1faf]
- RMP             [ARIMA Forecasting] [Arima Forecasting] [2008-12-15 19:16:19] [44ec60eb6065a3f81a5f756bd5af1faf]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
7.8
7.6
7.5
7.6
7.5
7.3
7.6
7.5
7.6
7.9
7.9
8.1
8.2
8
7.5
6.8
6.5
6.6
7.6
8
8
7.7
7.5
7.6
7.7
7.9
7.8
7.5
7.5
7.1
7.5
7.5
7.6
7.7
7.7
7.9
8.1
8.2
8.2
8.1
7.9
7.3
6.9
6.6
6.7
6.9
7
7.1
7.2
7.1
6.9
7
6.8
6.4
6.7
6.7
6.4
6.3
6.2
6.5

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=26867&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=26867&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=26867&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)0.302923728813559Range2Trim Var.0.218018867924528
V(Y[t],d=1,D=0)0.0755406195207481Range1.7Trim Var.0.0376560232220609
V(Y[t],d=2,D=0)0.0983454325468845Range1.5Trim Var.0.0544530612244898
V(Y[t],d=3,D=0)0.237293233082707Range2.7Trim Var.0.119137254901961
V(Y[t],d=0,D=1)0.345917553191489Range2.3Trim Var.0.244621951219512
V(Y[t],d=1,D=1)0.122146160962072Range1.5Trim Var.0.0689512195121951
V(Y[t],d=2,D=1)0.122202898550725Range1.4Trim Var.0.0722807017543859
V(Y[t],d=3,D=1)0.203313131313131Range2.00000000000000Trim Var.0.112631578947368
V(Y[t],d=0,D=2)0.84192857142857Range3.7Trim Var.0.555766129032258
V(Y[t],d=1,D=2)0.329865546218487Range2.8Trim Var.0.168279569892473
V(Y[t],d=2,D=2)0.314839572192513Range2.4Trim Var.0.182068965517241
V(Y[t],d=3,D=2)0.53996212121212Range3.09999999999999Trim Var.0.322586206896551

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 0.302923728813559 & Range & 2 & Trim Var. & 0.218018867924528 \tabularnewline
V(Y[t],d=1,D=0) & 0.0755406195207481 & Range & 1.7 & Trim Var. & 0.0376560232220609 \tabularnewline
V(Y[t],d=2,D=0) & 0.0983454325468845 & Range & 1.5 & Trim Var. & 0.0544530612244898 \tabularnewline
V(Y[t],d=3,D=0) & 0.237293233082707 & Range & 2.7 & Trim Var. & 0.119137254901961 \tabularnewline
V(Y[t],d=0,D=1) & 0.345917553191489 & Range & 2.3 & Trim Var. & 0.244621951219512 \tabularnewline
V(Y[t],d=1,D=1) & 0.122146160962072 & Range & 1.5 & Trim Var. & 0.0689512195121951 \tabularnewline
V(Y[t],d=2,D=1) & 0.122202898550725 & Range & 1.4 & Trim Var. & 0.0722807017543859 \tabularnewline
V(Y[t],d=3,D=1) & 0.203313131313131 & Range & 2.00000000000000 & Trim Var. & 0.112631578947368 \tabularnewline
V(Y[t],d=0,D=2) & 0.84192857142857 & Range & 3.7 & Trim Var. & 0.555766129032258 \tabularnewline
V(Y[t],d=1,D=2) & 0.329865546218487 & Range & 2.8 & Trim Var. & 0.168279569892473 \tabularnewline
V(Y[t],d=2,D=2) & 0.314839572192513 & Range & 2.4 & Trim Var. & 0.182068965517241 \tabularnewline
V(Y[t],d=3,D=2) & 0.53996212121212 & Range & 3.09999999999999 & Trim Var. & 0.322586206896551 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=26867&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]0.302923728813559[/C][C]Range[/C][C]2[/C][C]Trim Var.[/C][C]0.218018867924528[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]0.0755406195207481[/C][C]Range[/C][C]1.7[/C][C]Trim Var.[/C][C]0.0376560232220609[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]0.0983454325468845[/C][C]Range[/C][C]1.5[/C][C]Trim Var.[/C][C]0.0544530612244898[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]0.237293233082707[/C][C]Range[/C][C]2.7[/C][C]Trim Var.[/C][C]0.119137254901961[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]0.345917553191489[/C][C]Range[/C][C]2.3[/C][C]Trim Var.[/C][C]0.244621951219512[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]0.122146160962072[/C][C]Range[/C][C]1.5[/C][C]Trim Var.[/C][C]0.0689512195121951[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]0.122202898550725[/C][C]Range[/C][C]1.4[/C][C]Trim Var.[/C][C]0.0722807017543859[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]0.203313131313131[/C][C]Range[/C][C]2.00000000000000[/C][C]Trim Var.[/C][C]0.112631578947368[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]0.84192857142857[/C][C]Range[/C][C]3.7[/C][C]Trim Var.[/C][C]0.555766129032258[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]0.329865546218487[/C][C]Range[/C][C]2.8[/C][C]Trim Var.[/C][C]0.168279569892473[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]0.314839572192513[/C][C]Range[/C][C]2.4[/C][C]Trim Var.[/C][C]0.182068965517241[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]0.53996212121212[/C][C]Range[/C][C]3.09999999999999[/C][C]Trim Var.[/C][C]0.322586206896551[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=26867&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=26867&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)0.302923728813559Range2Trim Var.0.218018867924528
V(Y[t],d=1,D=0)0.0755406195207481Range1.7Trim Var.0.0376560232220609
V(Y[t],d=2,D=0)0.0983454325468845Range1.5Trim Var.0.0544530612244898
V(Y[t],d=3,D=0)0.237293233082707Range2.7Trim Var.0.119137254901961
V(Y[t],d=0,D=1)0.345917553191489Range2.3Trim Var.0.244621951219512
V(Y[t],d=1,D=1)0.122146160962072Range1.5Trim Var.0.0689512195121951
V(Y[t],d=2,D=1)0.122202898550725Range1.4Trim Var.0.0722807017543859
V(Y[t],d=3,D=1)0.203313131313131Range2.00000000000000Trim Var.0.112631578947368
V(Y[t],d=0,D=2)0.84192857142857Range3.7Trim Var.0.555766129032258
V(Y[t],d=1,D=2)0.329865546218487Range2.8Trim Var.0.168279569892473
V(Y[t],d=2,D=2)0.314839572192513Range2.4Trim Var.0.182068965517241
V(Y[t],d=3,D=2)0.53996212121212Range3.09999999999999Trim Var.0.322586206896551


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')