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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, 06 Dec 2011 13:50:08 -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/2011/Dec/06/t1323197416k5spc4k250z4b5p.htm/, Retrieved Mon, 29 Apr 2024 03:23:02 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=151796, Retrieved Mon, 29 Apr 2024 03:23:02 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact130

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [Univariate Data Series] [Identifying Integ...] [2009-11-22 12:08:06] [b98453cac15ba1066b407e146608df68]
- RMP         [Variance Reduction Matrix] [Births] [2010-11-29 09:39:41] [b98453cac15ba1066b407e146608df68]
F   PD          [Variance Reduction Matrix] [VRM cultuur] [2010-12-03 09:39:10] [74deae64b71f9d77c839af86f7c687b5]
- R                 [Variance Reduction Matrix] [] [2011-12-06 18:50:08] [4be1b05f688f7fa8db5b9e9e4d3a7e33] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
101.76
102.37
102.38
102.86
102.87
102.92
102.95
103.02
104.08
104.16
104.24
104.33
104.73
104.86
105.03
105.62
105.63
105.63
105.94
106.61
107.69
107.78
107.93
108.48
108.14
108.48
108.48
108.89
108.93
109.21
109.47
109.80
111.73
111.85
112.12
112.15
112.17
112.67
112.80
113.44
113.53
114.53
114.51
115.05
116.67
117.07
116.92
117.00
117.02
117.35
117.36
117.82
117.88
118.24
118.50
118.80
119.76
120.09

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'AstonUniversity' @ aston.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 & 'AstonUniversity' @ aston.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=151796&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]'AstonUniversity' @ aston.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=151796&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=151796&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'AstonUniversity' @ aston.wessa.net






Variance Reduction Matrix
V(Y[t],d=0,D=0)31.0793886267393Range18.33Trim Var.25.7738945701357
V(Y[t],d=1,D=0)0.167159962406016Range2.27000000000001Trim Var.0.072840078431373
V(Y[t],d=2,D=0)0.368014545454548Range3.41000000000003Trim Var.0.198583673469388
V(Y[t],d=3,D=0)1.12228303030304Range5.37000000000006Trim Var.0.643119472789118
V(Y[t],d=0,D=1)0.590323864734299Range2.83000000000001Trim Var.0.410429743589742
V(Y[t],d=1,D=1)0.115205555555557Range1.59000000000002Trim Var.0.0546114709851552
V(Y[t],d=2,D=1)0.287643710359412Range2.39000000000001Trim Var.0.164635064011381
V(Y[t],d=3,D=1)0.950991472868232Range4.16000000000005Trim Var.0.591966366366376
V(Y[t],d=0,D=2)1.02989162210339Range4.25999999999999Trim Var.0.609706781609198
V(Y[t],d=1,D=2)0.323225000000004Range2.46000000000002Trim Var.0.189835221674878
V(Y[t],d=2,D=2)0.908335483870984Range3.79000000000001Trim Var.0.572844841269856
V(Y[t],d=3,D=2)3.17597462365598Range6.43000000000005Trim Var.2.16512336182341

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 31.0793886267393 & Range & 18.33 & Trim Var. & 25.7738945701357 \tabularnewline
V(Y[t],d=1,D=0) & 0.167159962406016 & Range & 2.27000000000001 & Trim Var. & 0.072840078431373 \tabularnewline
V(Y[t],d=2,D=0) & 0.368014545454548 & Range & 3.41000000000003 & Trim Var. & 0.198583673469388 \tabularnewline
V(Y[t],d=3,D=0) & 1.12228303030304 & Range & 5.37000000000006 & Trim Var. & 0.643119472789118 \tabularnewline
V(Y[t],d=0,D=1) & 0.590323864734299 & Range & 2.83000000000001 & Trim Var. & 0.410429743589742 \tabularnewline
V(Y[t],d=1,D=1) & 0.115205555555557 & Range & 1.59000000000002 & Trim Var. & 0.0546114709851552 \tabularnewline
V(Y[t],d=2,D=1) & 0.287643710359412 & Range & 2.39000000000001 & Trim Var. & 0.164635064011381 \tabularnewline
V(Y[t],d=3,D=1) & 0.950991472868232 & Range & 4.16000000000005 & Trim Var. & 0.591966366366376 \tabularnewline
V(Y[t],d=0,D=2) & 1.02989162210339 & Range & 4.25999999999999 & Trim Var. & 0.609706781609198 \tabularnewline
V(Y[t],d=1,D=2) & 0.323225000000004 & Range & 2.46000000000002 & Trim Var. & 0.189835221674878 \tabularnewline
V(Y[t],d=2,D=2) & 0.908335483870984 & Range & 3.79000000000001 & Trim Var. & 0.572844841269856 \tabularnewline
V(Y[t],d=3,D=2) & 3.17597462365598 & Range & 6.43000000000005 & Trim Var. & 2.16512336182341 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=151796&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]31.0793886267393[/C][C]Range[/C][C]18.33[/C][C]Trim Var.[/C][C]25.7738945701357[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]0.167159962406016[/C][C]Range[/C][C]2.27000000000001[/C][C]Trim Var.[/C][C]0.072840078431373[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]0.368014545454548[/C][C]Range[/C][C]3.41000000000003[/C][C]Trim Var.[/C][C]0.198583673469388[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]1.12228303030304[/C][C]Range[/C][C]5.37000000000006[/C][C]Trim Var.[/C][C]0.643119472789118[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]0.590323864734299[/C][C]Range[/C][C]2.83000000000001[/C][C]Trim Var.[/C][C]0.410429743589742[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]0.115205555555557[/C][C]Range[/C][C]1.59000000000002[/C][C]Trim Var.[/C][C]0.0546114709851552[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]0.287643710359412[/C][C]Range[/C][C]2.39000000000001[/C][C]Trim Var.[/C][C]0.164635064011381[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]0.950991472868232[/C][C]Range[/C][C]4.16000000000005[/C][C]Trim Var.[/C][C]0.591966366366376[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]1.02989162210339[/C][C]Range[/C][C]4.25999999999999[/C][C]Trim Var.[/C][C]0.609706781609198[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]0.323225000000004[/C][C]Range[/C][C]2.46000000000002[/C][C]Trim Var.[/C][C]0.189835221674878[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]0.908335483870984[/C][C]Range[/C][C]3.79000000000001[/C][C]Trim Var.[/C][C]0.572844841269856[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]3.17597462365598[/C][C]Range[/C][C]6.43000000000005[/C][C]Trim Var.[/C][C]2.16512336182341[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=151796&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=151796&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)31.0793886267393Range18.33Trim Var.25.7738945701357
V(Y[t],d=1,D=0)0.167159962406016Range2.27000000000001Trim Var.0.072840078431373
V(Y[t],d=2,D=0)0.368014545454548Range3.41000000000003Trim Var.0.198583673469388
V(Y[t],d=3,D=0)1.12228303030304Range5.37000000000006Trim Var.0.643119472789118
V(Y[t],d=0,D=1)0.590323864734299Range2.83000000000001Trim Var.0.410429743589742
V(Y[t],d=1,D=1)0.115205555555557Range1.59000000000002Trim Var.0.0546114709851552
V(Y[t],d=2,D=1)0.287643710359412Range2.39000000000001Trim Var.0.164635064011381
V(Y[t],d=3,D=1)0.950991472868232Range4.16000000000005Trim Var.0.591966366366376
V(Y[t],d=0,D=2)1.02989162210339Range4.25999999999999Trim Var.0.609706781609198
V(Y[t],d=1,D=2)0.323225000000004Range2.46000000000002Trim Var.0.189835221674878
V(Y[t],d=2,D=2)0.908335483870984Range3.79000000000001Trim Var.0.572844841269856
V(Y[t],d=3,D=2)3.17597462365598Range6.43000000000005Trim Var.2.16512336182341


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')