FreeStatistics.org

Free Statistics

of Irreproducible Research!

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, 08 Dec 2008 17:17:49 -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/09/t1228781914vr5x8xmg3jsu95j.htm/, Retrieved Sun, 19 May 2024 12:01:04 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=31148, Retrieved Sun, 19 May 2024 12:01:04 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact197

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] [Run sequence plot...] [2008-12-02 22:19:27] [ed2ba3b6182103c15c0ab511ae4e6284]
- RMPD  [Standard Deviation-Mean Plot] [SD mean plot] [2008-12-06 11:49:39] [ed2ba3b6182103c15c0ab511ae4e6284]
F RM      [Variance Reduction Matrix] [variance reduction] [2008-12-06 12:44:59] [ed2ba3b6182103c15c0ab511ae4e6284]
-             [Variance Reduction Matrix] [variance reduction] [2008-12-09 00:17:49] [e8f764b122b426f433a1e1038b457077] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
92.66
94.2
94.37
94.45
94.62
94.37
93.43
94.79
94.88
94.79
94.62
94.71
93.77
95.73
95.99
95.82
95.47
95.82
94.71
96.33
96.5
96.16
96.33
96.33
95.05
96.84
96.92
97.44
97.78
97.69
96.67
98.29
98.2
98.71
98.54
98.2
96.92
99.06
99.65
99.82
99.99
100.33
99.31
101.1
101.1
100.93
100.85
100.93
99.6
101.88
101.81
102.38
102.74
102.82
101.72
103.47
102.98
102.68
102.9
103.03
101.29

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31148&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]2 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=31148&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31148&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 time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Variance Reduction Matrix
V(Y[t],d=0,D=0)9.34143142076503Range10.81Trim Var.7.20808236574746
V(Y[t],d=1,D=0)0.823979971751413Range4.02Trim Var.0.519069375907111
V(Y[t],d=2,D=0)2.21213886616014Range5.96000000000001Trim Var.1.52677851959361
V(Y[t],d=3,D=0)7.1888050816697Range10.9800000000000Trim Var.5.10669573906485
V(Y[t],d=0,D=1)0.366903569023567Range2.81999999999999Trim Var.0.240029591836733
V(Y[t],d=1,D=1)0.145123270440252Range1.72999999999999Trim Var.0.084811100832563
V(Y[t],d=2,D=1)0.230296298984036Range1.97000000000001Trim Var.0.160934505087882
V(Y[t],d=3,D=1)0.65524506033183Range3.34000000000000Trim Var.0.449334347826092
V(Y[t],d=0,D=2)1.09449515306122Range4.69Trim Var.0.667758139534875
V(Y[t],d=1,D=2)0.440875886524825Range2.68999999999993Trim Var.0.303400000000005
V(Y[t],d=2,D=2)0.610395097132292Range2.97000000000008Trim Var.0.419129756097559
V(Y[t],d=3,D=2)1.71511541062804Range4.77Trim Var.1.21632506410260

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 9.34143142076503 & Range & 10.81 & Trim Var. & 7.20808236574746 \tabularnewline
V(Y[t],d=1,D=0) & 0.823979971751413 & Range & 4.02 & Trim Var. & 0.519069375907111 \tabularnewline
V(Y[t],d=2,D=0) & 2.21213886616014 & Range & 5.96000000000001 & Trim Var. & 1.52677851959361 \tabularnewline
V(Y[t],d=3,D=0) & 7.1888050816697 & Range & 10.9800000000000 & Trim Var. & 5.10669573906485 \tabularnewline
V(Y[t],d=0,D=1) & 0.366903569023567 & Range & 2.81999999999999 & Trim Var. & 0.240029591836733 \tabularnewline
V(Y[t],d=1,D=1) & 0.145123270440252 & Range & 1.72999999999999 & Trim Var. & 0.084811100832563 \tabularnewline
V(Y[t],d=2,D=1) & 0.230296298984036 & Range & 1.97000000000001 & Trim Var. & 0.160934505087882 \tabularnewline
V(Y[t],d=3,D=1) & 0.65524506033183 & Range & 3.34000000000000 & Trim Var. & 0.449334347826092 \tabularnewline
V(Y[t],d=0,D=2) & 1.09449515306122 & Range & 4.69 & Trim Var. & 0.667758139534875 \tabularnewline
V(Y[t],d=1,D=2) & 0.440875886524825 & Range & 2.68999999999993 & Trim Var. & 0.303400000000005 \tabularnewline
V(Y[t],d=2,D=2) & 0.610395097132292 & Range & 2.97000000000008 & Trim Var. & 0.419129756097559 \tabularnewline
V(Y[t],d=3,D=2) & 1.71511541062804 & Range & 4.77 & Trim Var. & 1.21632506410260 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31148&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]9.34143142076503[/C][C]Range[/C][C]10.81[/C][C]Trim Var.[/C][C]7.20808236574746[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]0.823979971751413[/C][C]Range[/C][C]4.02[/C][C]Trim Var.[/C][C]0.519069375907111[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]2.21213886616014[/C][C]Range[/C][C]5.96000000000001[/C][C]Trim Var.[/C][C]1.52677851959361[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]7.1888050816697[/C][C]Range[/C][C]10.9800000000000[/C][C]Trim Var.[/C][C]5.10669573906485[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]0.366903569023567[/C][C]Range[/C][C]2.81999999999999[/C][C]Trim Var.[/C][C]0.240029591836733[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]0.145123270440252[/C][C]Range[/C][C]1.72999999999999[/C][C]Trim Var.[/C][C]0.084811100832563[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]0.230296298984036[/C][C]Range[/C][C]1.97000000000001[/C][C]Trim Var.[/C][C]0.160934505087882[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]0.65524506033183[/C][C]Range[/C][C]3.34000000000000[/C][C]Trim Var.[/C][C]0.449334347826092[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]1.09449515306122[/C][C]Range[/C][C]4.69[/C][C]Trim Var.[/C][C]0.667758139534875[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]0.440875886524825[/C][C]Range[/C][C]2.68999999999993[/C][C]Trim Var.[/C][C]0.303400000000005[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]0.610395097132292[/C][C]Range[/C][C]2.97000000000008[/C][C]Trim Var.[/C][C]0.419129756097559[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]1.71511541062804[/C][C]Range[/C][C]4.77[/C][C]Trim Var.[/C][C]1.21632506410260[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31148&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31148&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)9.34143142076503Range10.81Trim Var.7.20808236574746
V(Y[t],d=1,D=0)0.823979971751413Range4.02Trim Var.0.519069375907111
V(Y[t],d=2,D=0)2.21213886616014Range5.96000000000001Trim Var.1.52677851959361
V(Y[t],d=3,D=0)7.1888050816697Range10.9800000000000Trim Var.5.10669573906485
V(Y[t],d=0,D=1)0.366903569023567Range2.81999999999999Trim Var.0.240029591836733
V(Y[t],d=1,D=1)0.145123270440252Range1.72999999999999Trim Var.0.084811100832563
V(Y[t],d=2,D=1)0.230296298984036Range1.97000000000001Trim Var.0.160934505087882
V(Y[t],d=3,D=1)0.65524506033183Range3.34000000000000Trim Var.0.449334347826092
V(Y[t],d=0,D=2)1.09449515306122Range4.69Trim Var.0.667758139534875
V(Y[t],d=1,D=2)0.440875886524825Range2.68999999999993Trim Var.0.303400000000005
V(Y[t],d=2,D=2)0.610395097132292Range2.97000000000008Trim Var.0.419129756097559
V(Y[t],d=3,D=2)1.71511541062804Range4.77Trim Var.1.21632506410260


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 6 ;
Parameters (R input):
par1 = 6 ; par2 = ; par3 = ; par4 = ; par5 = ; par6 = ; par7 = ; par8 = ; par9 = ; par10 = ; par11 = ; par12 = ; par13 = ; par14 = ; par15 = ; par16 = ; par17 = ; par18 = ; par19 = ; par20 = ;
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')