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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, 28 Dec 2010 19:00:31 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/28/t12935627067uxf8o2ucfngxef.htm/, Retrieved Sat, 04 May 2024 22:23:32 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=116488, Retrieved Sat, 04 May 2024 22:23:32 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact126

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Kendall tau Correlation Matrix] [] [2010-12-05 18:04:16] [b98453cac15ba1066b407e146608df68]
F RMPD  [Pearson Correlation] [Pearson correlati...] [2010-12-22 19:14:03] [96348ef82925ade81ab3c243141d80f1]
- RMPD    [Variance Reduction Matrix] [variantie reducti...] [2010-12-24 14:01:07] [96348ef82925ade81ab3c243141d80f1]
-   PD      [Variance Reduction Matrix] [variantie reducti...] [2010-12-24 14:27:16] [96348ef82925ade81ab3c243141d80f1]
-    D        [Variance Reduction Matrix] [VRM goudprijzen] [2010-12-24 16:59:39] [96348ef82925ade81ab3c243141d80f1]
-    D            [Variance Reduction Matrix] [VRM goudprijzen] [2010-12-28 19:00:31] [694c30abd2a3b2ee5cb46fc74cb5bfb9] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
336.02
333.15
314.95
302.48
307.31
305.50
308.57
322.58
337.09
323.81
333.06
331.90
327.90
319.93
331.51
336.42
319.77
323.20
324.51
328.34
331.88
336.45
337.95
330.75
323.87
325.26
328.73
331.72
332.54
354.25
352.69
356.15
372.50
390.90
404.65
430.04
453.54
464.98
463.31
497.20
528.62
470.91
499.53
493.51
469.97
464.41
487.15
476.45
484.91
509.61
495.19
504.75
493.43
488.58
484.82
488.46
512.32
530.29
549.38
551.45
604.41
625.29
623.56
577.42
572.28
571.69
596.28
560.00
577.93
606.51
597.31
607.58
648.14
737.48
708.73
674.01
679.90
674.93
663.38
665.69
684.21
703.71
755.42
772.43

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'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116488&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116488&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116488&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Variance Reduction Matrix
V(Y[t],d=0,D=0)18339.9765336059Range469.95Trim Var.14117.0641104961
V(Y[t],d=1,D=0)443.543114046429Range147.05Trim Var.162.673338812785
V(Y[t],d=2,D=0)845.582734718457Range204.42Trim Var.313.306156787949
V(Y[t],d=3,D=0)2388.88884799382Range342.33Trim Var.833.091497102615
V(Y[t],d=0,D=1)2800.58492940141Range231.27Trim Var.1974.46310116567
V(Y[t],d=1,D=1)702.891461046277Range147.88Trim Var.370.058928929851
V(Y[t],d=2,D=1)1710.51889780538Range219.62Trim Var.845.70200179799
V(Y[t],d=3,D=1)5396.82380848252Range400.46Trim Var.2769.80888333333
V(Y[t],d=0,D=2)7278.04950836158Range414.58Trim Var.4497.06120628931
V(Y[t],d=1,D=2)2176.40555037989Range229.98Trim Var.1416.88491552975
V(Y[t],d=2,D=2)5383.91394797337Range400.46Trim Var.3218.81864053544
V(Y[t],d=3,D=2)17480.1209776316Range676.999999999999Trim Var.10542.4047078431

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 18339.9765336059 & Range & 469.95 & Trim Var. & 14117.0641104961 \tabularnewline
V(Y[t],d=1,D=0) & 443.543114046429 & Range & 147.05 & Trim Var. & 162.673338812785 \tabularnewline
V(Y[t],d=2,D=0) & 845.582734718457 & Range & 204.42 & Trim Var. & 313.306156787949 \tabularnewline
V(Y[t],d=3,D=0) & 2388.88884799382 & Range & 342.33 & Trim Var. & 833.091497102615 \tabularnewline
V(Y[t],d=0,D=1) & 2800.58492940141 & Range & 231.27 & Trim Var. & 1974.46310116567 \tabularnewline
V(Y[t],d=1,D=1) & 702.891461046277 & Range & 147.88 & Trim Var. & 370.058928929851 \tabularnewline
V(Y[t],d=2,D=1) & 1710.51889780538 & Range & 219.62 & Trim Var. & 845.70200179799 \tabularnewline
V(Y[t],d=3,D=1) & 5396.82380848252 & Range & 400.46 & Trim Var. & 2769.80888333333 \tabularnewline
V(Y[t],d=0,D=2) & 7278.04950836158 & Range & 414.58 & Trim Var. & 4497.06120628931 \tabularnewline
V(Y[t],d=1,D=2) & 2176.40555037989 & Range & 229.98 & Trim Var. & 1416.88491552975 \tabularnewline
V(Y[t],d=2,D=2) & 5383.91394797337 & Range & 400.46 & Trim Var. & 3218.81864053544 \tabularnewline
V(Y[t],d=3,D=2) & 17480.1209776316 & Range & 676.999999999999 & Trim Var. & 10542.4047078431 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=116488&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]18339.9765336059[/C][C]Range[/C][C]469.95[/C][C]Trim Var.[/C][C]14117.0641104961[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]443.543114046429[/C][C]Range[/C][C]147.05[/C][C]Trim Var.[/C][C]162.673338812785[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]845.582734718457[/C][C]Range[/C][C]204.42[/C][C]Trim Var.[/C][C]313.306156787949[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]2388.88884799382[/C][C]Range[/C][C]342.33[/C][C]Trim Var.[/C][C]833.091497102615[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]2800.58492940141[/C][C]Range[/C][C]231.27[/C][C]Trim Var.[/C][C]1974.46310116567[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]702.891461046277[/C][C]Range[/C][C]147.88[/C][C]Trim Var.[/C][C]370.058928929851[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]1710.51889780538[/C][C]Range[/C][C]219.62[/C][C]Trim Var.[/C][C]845.70200179799[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]5396.82380848252[/C][C]Range[/C][C]400.46[/C][C]Trim Var.[/C][C]2769.80888333333[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]7278.04950836158[/C][C]Range[/C][C]414.58[/C][C]Trim Var.[/C][C]4497.06120628931[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]2176.40555037989[/C][C]Range[/C][C]229.98[/C][C]Trim Var.[/C][C]1416.88491552975[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]5383.91394797337[/C][C]Range[/C][C]400.46[/C][C]Trim Var.[/C][C]3218.81864053544[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]17480.1209776316[/C][C]Range[/C][C]676.999999999999[/C][C]Trim Var.[/C][C]10542.4047078431[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=116488&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=116488&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)18339.9765336059Range469.95Trim Var.14117.0641104961
V(Y[t],d=1,D=0)443.543114046429Range147.05Trim Var.162.673338812785
V(Y[t],d=2,D=0)845.582734718457Range204.42Trim Var.313.306156787949
V(Y[t],d=3,D=0)2388.88884799382Range342.33Trim Var.833.091497102615
V(Y[t],d=0,D=1)2800.58492940141Range231.27Trim Var.1974.46310116567
V(Y[t],d=1,D=1)702.891461046277Range147.88Trim Var.370.058928929851
V(Y[t],d=2,D=1)1710.51889780538Range219.62Trim Var.845.70200179799
V(Y[t],d=3,D=1)5396.82380848252Range400.46Trim Var.2769.80888333333
V(Y[t],d=0,D=2)7278.04950836158Range414.58Trim Var.4497.06120628931
V(Y[t],d=1,D=2)2176.40555037989Range229.98Trim Var.1416.88491552975
V(Y[t],d=2,D=2)5383.91394797337Range400.46Trim Var.3218.81864053544
V(Y[t],d=3,D=2)17480.1209776316Range676.999999999999Trim Var.10542.4047078431


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(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()