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 computationSun, 13 Dec 2009 08:17:24 -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/2009/Dec/13/t1260717468kdm2p91vog52h97.htm/, Retrieved Sat, 27 Apr 2024 20:55:52 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=67322, Retrieved Sat, 27 Apr 2024 20:55:52 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact109

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       [Variance Reduction Matrix] [Identifying Integ...] [2009-11-22 12:29:54] [b98453cac15ba1066b407e146608df68]
-    D        [Variance Reduction Matrix] [WS8 Method 2] [2009-11-25 16:22:46] [445b292c553470d9fed8bc2796fd3a00]
-    D          [Variance Reduction Matrix] [ws 8 vrm] [2009-11-25 21:32:07] [134dc66689e3d457a82860db6471d419]
-    D              [Variance Reduction Matrix] [WS8] [2009-12-13 15:17:24] [5cd0e65b1f56b3935a0672588b930e12] [Current]
-    D                [Variance Reduction Matrix] [WS9] [2009-12-13 19:07:04] [85be98bd9ebcfd4d73e77f8552419c9a]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
 181.10 
 191.20 
 206.20 
 212.00 
 224.70 
 231.30 
 229.30 
 227.40 
 253.90 
 265.90 
 277.70 
 292.10 
 282.90 
 292.80 
 311.00 
 330.90 
 350.00 
 348.50 
 360.90 
 345.90 
 308.80 
 320.00 
 322.00 
 322.90 
 343.30 
 354.70 
 376.60 
 383.20 
 392.50 
 388.20 
 407.40 
 412.50 
 419.80 
 418.10 
 389.20 
 391.60 
 412.90 
 385.90 
 385.50 
 350.20 
 336.30 
 318.50 
 345.40 
 377.40 
 359.50 
 315.60 
 307.80 
 277.40 
 186.90 
 160.00 
 149.10 
 148.90 
 137.90 
 134.00 
 157.50 
 175.10 
 181.00 
 182.20 
 207.80 
 219.40

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'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67322&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67322&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67322&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'Gwilym Jenkins' @ 72.249.127.135






Variance Reduction Matrix
V(Y[t],d=0,D=0)7377.27867514124Range285.8Trim Var.6017.34488120196
V(Y[t],d=1,D=0)450.79081823495Range122.5Trim Var.229.519462989840
V(Y[t],d=2,D=0)563.829670296431Range123.7Trim Var.300.53496229261
V(Y[t],d=3,D=0)1501.66219924812Range190.900000000000Trim Var.925.79331764706
V(Y[t],d=0,D=1)13284.6560106383Range368Trim Var.10400.5825377468
V(Y[t],d=1,D=1)828.34347826087Range156.9Trim Var.360.505743902439
V(Y[t],d=2,D=1)1216.73791304348Range190.900000000000Trim Var.561.264
V(Y[t],d=3,D=1)3319.27861616162Range313.4Trim Var.1443.00430499325
V(Y[t],d=0,D=2)7606.488Range351.8Trim Var.4938.50064516129
V(Y[t],d=1,D=2)1986.11927731092Range220.70Trim Var.1024.62012903226
V(Y[t],d=2,D=2)3233.84439393939Range271.300000000000Trim Var.1859.95402298850
V(Y[t],d=3,D=2)8705.6984280303Range424.499999999999Trim Var.4902.94280788178

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 7377.27867514124 & Range & 285.8 & Trim Var. & 6017.34488120196 \tabularnewline
V(Y[t],d=1,D=0) & 450.79081823495 & Range & 122.5 & Trim Var. & 229.519462989840 \tabularnewline
V(Y[t],d=2,D=0) & 563.829670296431 & Range & 123.7 & Trim Var. & 300.53496229261 \tabularnewline
V(Y[t],d=3,D=0) & 1501.66219924812 & Range & 190.900000000000 & Trim Var. & 925.79331764706 \tabularnewline
V(Y[t],d=0,D=1) & 13284.6560106383 & Range & 368 & Trim Var. & 10400.5825377468 \tabularnewline
V(Y[t],d=1,D=1) & 828.34347826087 & Range & 156.9 & Trim Var. & 360.505743902439 \tabularnewline
V(Y[t],d=2,D=1) & 1216.73791304348 & Range & 190.900000000000 & Trim Var. & 561.264 \tabularnewline
V(Y[t],d=3,D=1) & 3319.27861616162 & Range & 313.4 & Trim Var. & 1443.00430499325 \tabularnewline
V(Y[t],d=0,D=2) & 7606.488 & Range & 351.8 & Trim Var. & 4938.50064516129 \tabularnewline
V(Y[t],d=1,D=2) & 1986.11927731092 & Range & 220.70 & Trim Var. & 1024.62012903226 \tabularnewline
V(Y[t],d=2,D=2) & 3233.84439393939 & Range & 271.300000000000 & Trim Var. & 1859.95402298850 \tabularnewline
V(Y[t],d=3,D=2) & 8705.6984280303 & Range & 424.499999999999 & Trim Var. & 4902.94280788178 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67322&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]7377.27867514124[/C][C]Range[/C][C]285.8[/C][C]Trim Var.[/C][C]6017.34488120196[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]450.79081823495[/C][C]Range[/C][C]122.5[/C][C]Trim Var.[/C][C]229.519462989840[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]563.829670296431[/C][C]Range[/C][C]123.7[/C][C]Trim Var.[/C][C]300.53496229261[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]1501.66219924812[/C][C]Range[/C][C]190.900000000000[/C][C]Trim Var.[/C][C]925.79331764706[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]13284.6560106383[/C][C]Range[/C][C]368[/C][C]Trim Var.[/C][C]10400.5825377468[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]828.34347826087[/C][C]Range[/C][C]156.9[/C][C]Trim Var.[/C][C]360.505743902439[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]1216.73791304348[/C][C]Range[/C][C]190.900000000000[/C][C]Trim Var.[/C][C]561.264[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]3319.27861616162[/C][C]Range[/C][C]313.4[/C][C]Trim Var.[/C][C]1443.00430499325[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]7606.488[/C][C]Range[/C][C]351.8[/C][C]Trim Var.[/C][C]4938.50064516129[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]1986.11927731092[/C][C]Range[/C][C]220.70[/C][C]Trim Var.[/C][C]1024.62012903226[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]3233.84439393939[/C][C]Range[/C][C]271.300000000000[/C][C]Trim Var.[/C][C]1859.95402298850[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]8705.6984280303[/C][C]Range[/C][C]424.499999999999[/C][C]Trim Var.[/C][C]4902.94280788178[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67322&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67322&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)7377.27867514124Range285.8Trim Var.6017.34488120196
V(Y[t],d=1,D=0)450.79081823495Range122.5Trim Var.229.519462989840
V(Y[t],d=2,D=0)563.829670296431Range123.7Trim Var.300.53496229261
V(Y[t],d=3,D=0)1501.66219924812Range190.900000000000Trim Var.925.79331764706
V(Y[t],d=0,D=1)13284.6560106383Range368Trim Var.10400.5825377468
V(Y[t],d=1,D=1)828.34347826087Range156.9Trim Var.360.505743902439
V(Y[t],d=2,D=1)1216.73791304348Range190.900000000000Trim Var.561.264
V(Y[t],d=3,D=1)3319.27861616162Range313.4Trim Var.1443.00430499325
V(Y[t],d=0,D=2)7606.488Range351.8Trim Var.4938.50064516129
V(Y[t],d=1,D=2)1986.11927731092Range220.70Trim Var.1024.62012903226
V(Y[t],d=2,D=2)3233.84439393939Range271.300000000000Trim Var.1859.95402298850
V(Y[t],d=3,D=2)8705.6984280303Range424.499999999999Trim Var.4902.94280788178


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')