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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, 02 Dec 2008 00:22:03 -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/02/t1228202578s8jzexcr5elg7b8.htm/, Retrieved Tue, 28 May 2024 01:04:42 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=27565, Retrieved Tue, 28 May 2024 01:04:42 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact243

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Data Series] [Airline data] [2007-10-18 09:58:47] [42daae401fd3def69a25014f2252b4c2]
F RMPD  [Variance Reduction Matrix] [Non Stationary Ti...] [2008-12-01 17:48:47] [b943bd7078334192ff8343563ee31113]
- RMP     [Spectral Analysis] [Non Stationary Ti...] [2008-12-01 19:56:04] [b943bd7078334192ff8343563ee31113]
- RMPD      [Cross Correlation Function] [Non Stationary Ti...] [2008-12-01 20:13:53] [b943bd7078334192ff8343563ee31113]
- RMPD        [(Partial) Autocorrelation Function] [Non Stationary Ti...] [2008-12-01 20:27:10] [b943bd7078334192ff8343563ee31113]
-   PD          [(Partial) Autocorrelation Function] [Non Stationary Ti...] [2008-12-01 20:29:06] [b943bd7078334192ff8343563ee31113]
-   P             [(Partial) Autocorrelation Function] [Non Stationary Ti...] [2008-12-01 20:31:48] [b943bd7078334192ff8343563ee31113]
- RMP               [Variance Reduction Matrix] [Non Stationary Ti...] [2008-12-01 20:34:07] [b943bd7078334192ff8343563ee31113]
- RMP                 [Spectral Analysis] [Non Stationary Ti...] [2008-12-01 20:37:58] [b943bd7078334192ff8343563ee31113]
- RMP                   [Standard Deviation-Mean Plot] [Non Stationary Ti...] [2008-12-01 20:41:45] [b943bd7078334192ff8343563ee31113]
- RMPD                    [(Partial) Autocorrelation Function] [Non Stationary Ti...] [2008-12-02 07:15:23] [b943bd7078334192ff8343563ee31113]
-   PD                      [(Partial) Autocorrelation Function] [Non Stationary Ti...] [2008-12-02 07:17:05] [b943bd7078334192ff8343563ee31113]
-   P                         [(Partial) Autocorrelation Function] [Non Stationary Ti...] [2008-12-02 07:19:06] [b943bd7078334192ff8343563ee31113]
- RMP                             [Variance Reduction Matrix] [Non Stationary Ti...] [2008-12-02 07:22:03] [620b6ad5c4696049e39cb73ce029682c] [Current]
- RMP                               [Spectral Analysis] [Non Stationary Ti...] [2008-12-02 07:25:43] [b943bd7078334192ff8343563ee31113]
- RMP                                 [Standard Deviation-Mean Plot] [Non Stationary Ti...] [2008-12-02 07:32:20] [b943bd7078334192ff8343563ee31113]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0.8721
0.8552
0.8564
0.8973
0.9383
0.9217
0.9095
0.892
0.8742
0.8532
0.8607
0.9005
0.9111
0.9059
0.8883
0.8924
0.8833
0.87
0.8758
0.8858
0.917
0.9554
0.9922
0.9778
0.9808
0.9811
1.0014
1.0183
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
1.4718
1.4748
1.5527
1.575
1.5557
1.5553
1.577
1.4975
1.4369

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'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=27565&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]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=27565&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27565&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'Herman Ole Andreas Wold' @ 193.190.124.10:1001






Variance Reduction Matrix
V(Y[t],d=0,D=0)0.0405081902040378Range0.7238Trim Var.0.0306534003394814
V(Y[t],d=1,D=0)0.000742842035087718Range0.157400000000000Trim Var.0.000421444213406292
V(Y[t],d=2,D=0)0.00105157285106383Range0.176100000000000Trim Var.0.000658638767507
V(Y[t],d=3,D=0)0.00263264680851063Range0.254700000000000Trim Var.0.00159273406052782
V(Y[t],d=0,D=1)0.00807656947619047Range0.3964Trim Var.0.00494071220900901
V(Y[t],d=1,D=1)0.00139161795037292Range0.162300000000000Trim Var.0.000946697484265085
V(Y[t],d=2,D=1)0.00195925987657948Range0.1718Trim Var.0.00144855962709284
V(Y[t],d=3,D=1)0.00487131906052391Range0.291999999999999Trim Var.0.00308430211071986
V(Y[t],d=0,D=2)0.0166345962975647Range0.5583Trim Var.0.0111455495288461
V(Y[t],d=1,D=2)0.00381122290884193Range0.247599999999999Trim Var.0.00254910386656746
V(Y[t],d=2,D=2)0.00591530906639836Range0.313699999999999Trim Var.0.00423864152073731
V(Y[t],d=3,D=2)0.0150454580559005Range0.554199999999998Trim Var.0.0097560339740877

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 0.0405081902040378 & Range & 0.7238 & Trim Var. & 0.0306534003394814 \tabularnewline
V(Y[t],d=1,D=0) & 0.000742842035087718 & Range & 0.157400000000000 & Trim Var. & 0.000421444213406292 \tabularnewline
V(Y[t],d=2,D=0) & 0.00105157285106383 & Range & 0.176100000000000 & Trim Var. & 0.000658638767507 \tabularnewline
V(Y[t],d=3,D=0) & 0.00263264680851063 & Range & 0.254700000000000 & Trim Var. & 0.00159273406052782 \tabularnewline
V(Y[t],d=0,D=1) & 0.00807656947619047 & Range & 0.3964 & Trim Var. & 0.00494071220900901 \tabularnewline
V(Y[t],d=1,D=1) & 0.00139161795037292 & Range & 0.162300000000000 & Trim Var. & 0.000946697484265085 \tabularnewline
V(Y[t],d=2,D=1) & 0.00195925987657948 & Range & 0.1718 & Trim Var. & 0.00144855962709284 \tabularnewline
V(Y[t],d=3,D=1) & 0.00487131906052391 & Range & 0.291999999999999 & Trim Var. & 0.00308430211071986 \tabularnewline
V(Y[t],d=0,D=2) & 0.0166345962975647 & Range & 0.5583 & Trim Var. & 0.0111455495288461 \tabularnewline
V(Y[t],d=1,D=2) & 0.00381122290884193 & Range & 0.247599999999999 & Trim Var. & 0.00254910386656746 \tabularnewline
V(Y[t],d=2,D=2) & 0.00591530906639836 & Range & 0.313699999999999 & Trim Var. & 0.00423864152073731 \tabularnewline
V(Y[t],d=3,D=2) & 0.0150454580559005 & Range & 0.554199999999998 & Trim Var. & 0.0097560339740877 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=27565&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]0.0405081902040378[/C][C]Range[/C][C]0.7238[/C][C]Trim Var.[/C][C]0.0306534003394814[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]0.000742842035087718[/C][C]Range[/C][C]0.157400000000000[/C][C]Trim Var.[/C][C]0.000421444213406292[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]0.00105157285106383[/C][C]Range[/C][C]0.176100000000000[/C][C]Trim Var.[/C][C]0.000658638767507[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]0.00263264680851063[/C][C]Range[/C][C]0.254700000000000[/C][C]Trim Var.[/C][C]0.00159273406052782[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]0.00807656947619047[/C][C]Range[/C][C]0.3964[/C][C]Trim Var.[/C][C]0.00494071220900901[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]0.00139161795037292[/C][C]Range[/C][C]0.162300000000000[/C][C]Trim Var.[/C][C]0.000946697484265085[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]0.00195925987657948[/C][C]Range[/C][C]0.1718[/C][C]Trim Var.[/C][C]0.00144855962709284[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]0.00487131906052391[/C][C]Range[/C][C]0.291999999999999[/C][C]Trim Var.[/C][C]0.00308430211071986[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]0.0166345962975647[/C][C]Range[/C][C]0.5583[/C][C]Trim Var.[/C][C]0.0111455495288461[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]0.00381122290884193[/C][C]Range[/C][C]0.247599999999999[/C][C]Trim Var.[/C][C]0.00254910386656746[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]0.00591530906639836[/C][C]Range[/C][C]0.313699999999999[/C][C]Trim Var.[/C][C]0.00423864152073731[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]0.0150454580559005[/C][C]Range[/C][C]0.554199999999998[/C][C]Trim Var.[/C][C]0.0097560339740877[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=27565&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27565&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)0.0405081902040378Range0.7238Trim Var.0.0306534003394814
V(Y[t],d=1,D=0)0.000742842035087718Range0.157400000000000Trim Var.0.000421444213406292
V(Y[t],d=2,D=0)0.00105157285106383Range0.176100000000000Trim Var.0.000658638767507
V(Y[t],d=3,D=0)0.00263264680851063Range0.254700000000000Trim Var.0.00159273406052782
V(Y[t],d=0,D=1)0.00807656947619047Range0.3964Trim Var.0.00494071220900901
V(Y[t],d=1,D=1)0.00139161795037292Range0.162300000000000Trim Var.0.000946697484265085
V(Y[t],d=2,D=1)0.00195925987657948Range0.1718Trim Var.0.00144855962709284
V(Y[t],d=3,D=1)0.00487131906052391Range0.291999999999999Trim Var.0.00308430211071986
V(Y[t],d=0,D=2)0.0166345962975647Range0.5583Trim Var.0.0111455495288461
V(Y[t],d=1,D=2)0.00381122290884193Range0.247599999999999Trim Var.0.00254910386656746
V(Y[t],d=2,D=2)0.00591530906639836Range0.313699999999999Trim Var.0.00423864152073731
V(Y[t],d=3,D=2)0.0150454580559005Range0.554199999999998Trim Var.0.0097560339740877


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')