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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 computationSun, 16 Dec 2012 14:53:49 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Dec/16/t1355687658g6fy530xddu87qi.htm/, Retrieved Fri, 19 Apr 2024 16:39:24 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=200562, Retrieved Fri, 19 Apr 2024 16:39:24 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact143

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [] [2008-12-08 19:22:39] [d2d412c7f4d35ffbf5ee5ee89db327d4]
- RMP   [Spectral Analysis] [] [2011-12-06 19:48:28] [b98453cac15ba1066b407e146608df68]
- R PD    [Spectral Analysis] [] [2011-12-14 15:31:08] [c53df38315e3cbde2dbe0de809195ef2]
-   P       [Spectral Analysis] [] [2011-12-14 15:41:56] [c53df38315e3cbde2dbe0de809195ef2]
- RMP           [Variance Reduction Matrix] [paper deel 4 VRM] [2012-12-16 19:53:49] [292b44c97cfd231f70174a072f53fc18] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1.262
1.743
1.964
3.258
4.966
4.944
5.907
5.561
5.321
3.582
1.757
1.894
1.442
2.238
2.179
3.218
5.139
4.990
4.914
6.084
5.672
3.548
1.793
2.086
1.376
2.202
2.683
3.303
5.202
5.231
4.880
7.998
4.977
3.531
2.025
2.205
1.504
2.090
2.702
2.939
4.500
6.208
6.415
5.657
5.964
3.163
1.997
2.422
1.507
1.992
2.487
3.490
4.647
5.594
5.611
5.788
6.204
3.013
1.931
2.549
1.580
2.111
2.192
3.601
4.665
4.876
5.813
5.589
5.331
3.075
2.002
2.306
1.594
2.467
2.222
3.607
4.685
4.962
5.770
5.480
5.000
3.228
1.993
2.288
1.351
2.218
2.461
3.028
4.784
4.975
4.607
6.249
4.809
3.157
1.910
2.228
1.169
2.154
2.249
2.687
4.359
5.382
4.459
6.398
4.596
3.024
1.887
2.070
1.511
2.059
2.635
2.867
4.403
5.720
4.502
5.749
5.627
2.846
1.762
2.429
1.579
2.146
2.462
3.695
4.831
5.134
6.250
5.760
6.249
2.917
1.741
2.359

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'Gertrude Mary Cox' @ cox.wessa.net

\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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=200562&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=200562&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=200562&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'Gertrude Mary Cox' @ cox.wessa.net






Variance Reduction Matrix
V(Y[t],d=0,D=0)2.65149672935461Range6.829Trim Var.2.13287772504708
V(Y[t],d=1,D=0)1.38043595901351Range6.45Trim Var.0.808715120394931
V(Y[t],d=2,D=0)2.34916285754323Range9.608Trim Var.1.33070068208396
V(Y[t],d=3,D=0)6.9041226658188Range17.322Trim Var.3.81103355865751
V(Y[t],d=0,D=1)0.25372967394958Range4.255Trim Var.0.0788004866735895
V(Y[t],d=1,D=1)0.677308057541661Range7.204Trim Var.0.195185345794392
V(Y[t],d=2,D=1)2.19713349703028Range11.887Trim Var.0.62556961509434
V(Y[t],d=3,D=1)7.50409916371942Range23.525Trim Var.2.23802760622711
V(Y[t],d=0,D=2)0.602169802959502Range6.727Trim Var.0.177552690789474
V(Y[t],d=1,D=2)1.63934839640275Range11.761Trim Var.0.37284283493841
V(Y[t],d=2,D=2)5.20355832165319Range19.791Trim Var.1.26321899576756
V(Y[t],d=3,D=2)17.5165863457875Range38.149Trim Var.4.38678601075269

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 2.65149672935461 & Range & 6.829 & Trim Var. & 2.13287772504708 \tabularnewline
V(Y[t],d=1,D=0) & 1.38043595901351 & Range & 6.45 & Trim Var. & 0.808715120394931 \tabularnewline
V(Y[t],d=2,D=0) & 2.34916285754323 & Range & 9.608 & Trim Var. & 1.33070068208396 \tabularnewline
V(Y[t],d=3,D=0) & 6.9041226658188 & Range & 17.322 & Trim Var. & 3.81103355865751 \tabularnewline
V(Y[t],d=0,D=1) & 0.25372967394958 & Range & 4.255 & Trim Var. & 0.0788004866735895 \tabularnewline
V(Y[t],d=1,D=1) & 0.677308057541661 & Range & 7.204 & Trim Var. & 0.195185345794392 \tabularnewline
V(Y[t],d=2,D=1) & 2.19713349703028 & Range & 11.887 & Trim Var. & 0.62556961509434 \tabularnewline
V(Y[t],d=3,D=1) & 7.50409916371942 & Range & 23.525 & Trim Var. & 2.23802760622711 \tabularnewline
V(Y[t],d=0,D=2) & 0.602169802959502 & Range & 6.727 & Trim Var. & 0.177552690789474 \tabularnewline
V(Y[t],d=1,D=2) & 1.63934839640275 & Range & 11.761 & Trim Var. & 0.37284283493841 \tabularnewline
V(Y[t],d=2,D=2) & 5.20355832165319 & Range & 19.791 & Trim Var. & 1.26321899576756 \tabularnewline
V(Y[t],d=3,D=2) & 17.5165863457875 & Range & 38.149 & Trim Var. & 4.38678601075269 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=200562&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]2.65149672935461[/C][C]Range[/C][C]6.829[/C][C]Trim Var.[/C][C]2.13287772504708[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]1.38043595901351[/C][C]Range[/C][C]6.45[/C][C]Trim Var.[/C][C]0.808715120394931[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]2.34916285754323[/C][C]Range[/C][C]9.608[/C][C]Trim Var.[/C][C]1.33070068208396[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]6.9041226658188[/C][C]Range[/C][C]17.322[/C][C]Trim Var.[/C][C]3.81103355865751[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]0.25372967394958[/C][C]Range[/C][C]4.255[/C][C]Trim Var.[/C][C]0.0788004866735895[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]0.677308057541661[/C][C]Range[/C][C]7.204[/C][C]Trim Var.[/C][C]0.195185345794392[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]2.19713349703028[/C][C]Range[/C][C]11.887[/C][C]Trim Var.[/C][C]0.62556961509434[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]7.50409916371942[/C][C]Range[/C][C]23.525[/C][C]Trim Var.[/C][C]2.23802760622711[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]0.602169802959502[/C][C]Range[/C][C]6.727[/C][C]Trim Var.[/C][C]0.177552690789474[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]1.63934839640275[/C][C]Range[/C][C]11.761[/C][C]Trim Var.[/C][C]0.37284283493841[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]5.20355832165319[/C][C]Range[/C][C]19.791[/C][C]Trim Var.[/C][C]1.26321899576756[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]17.5165863457875[/C][C]Range[/C][C]38.149[/C][C]Trim Var.[/C][C]4.38678601075269[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=200562&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=200562&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)2.65149672935461Range6.829Trim Var.2.13287772504708
V(Y[t],d=1,D=0)1.38043595901351Range6.45Trim Var.0.808715120394931
V(Y[t],d=2,D=0)2.34916285754323Range9.608Trim Var.1.33070068208396
V(Y[t],d=3,D=0)6.9041226658188Range17.322Trim Var.3.81103355865751
V(Y[t],d=0,D=1)0.25372967394958Range4.255Trim Var.0.0788004866735895
V(Y[t],d=1,D=1)0.677308057541661Range7.204Trim Var.0.195185345794392
V(Y[t],d=2,D=1)2.19713349703028Range11.887Trim Var.0.62556961509434
V(Y[t],d=3,D=1)7.50409916371942Range23.525Trim Var.2.23802760622711
V(Y[t],d=0,D=2)0.602169802959502Range6.727Trim Var.0.177552690789474
V(Y[t],d=1,D=2)1.63934839640275Range11.761Trim Var.0.37284283493841
V(Y[t],d=2,D=2)5.20355832165319Range19.791Trim Var.1.26321899576756
V(Y[t],d=3,D=2)17.5165863457875Range38.149Trim Var.4.38678601075269


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 <- '1'
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(myx,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')
bitmap(file='pic0.png')
op <- par(mfrow=c(2,2))
plot(x,type='l',xlab='time',ylab='value',main='d=0, D=0')
plot(diff(x,lag=1,differences=1),type='l',xlab='time',ylab='value',main='d=1, D=0')
plot(diff(x,lag=par1,differences=1),type='l',xlab='time',ylab='value',main='d=0, D=1')
plot(diff(diff(x,lag=1,differences=1),lag=par1,differences=1),type='l',xlab='time',ylab='value',main='d=1, D=1')
par(op)
dev.off()