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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_variancereduction.wasp
Title produced by softwareVariance Reduction Matrix
Date of computationTue, 09 Dec 2008 10:07:48 -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/t1228842524o5ds544oqx81z3n.htm/, Retrieved Fri, 17 May 2024 02:39:12 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=31592, Retrieved Fri, 17 May 2024 02:39:12 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact204

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [Variance Reduction Matrix] [Toon Wouters] [2008-12-09 17:07:48] [14e94996a4178d938cb12bed20a4a373] [Current]
Feedback Forum
2008-12-15 18:44:42 [Steven Vercammen] [reply] 
Dit klopt.De variantie reductie matrix geeft de varianties weer na differentiatie, optimaal is dat de variantie zo klein mogelijk is omdat we dan zoveel mogelijk kunnen verklaren. De variantie is hier optimaal bij d=0 en D=1. Als er sprake is van veel outliers moeten we kijken naar de getrimde variantie waarbij de 5% uiterste waarden worden weggelaten.

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
94
118.6
135
132.7
110.1
111
159.4
129.9
124.8
140.5
120.6
121.6
107.3
130.7
134.9
128.3
99.8
96.7
134.1
131.6
118
133.2
109.3
111.9
98.3
116.3
113.6
121.3
93.7
92.3
132
114.3
123.1
117.3
106
107.5
104.3
112.6
113.9
132.8
88.8
97.7
131.2
116.1
124.7
128.2
105
102.3
98.4
111.1
125.3
123.6
86.7
100.6
123.3
112.2
120.8
114.8
107.3
107.5
93.1
112.4
127.9
120.7
91
98.5
118.9
113.8
113.8
118.7
105.1
101.4
84.1
107.2
119.9
105.4
88.6
90.5
108.5
104.7
100
113.1
96.7
98.5

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'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31592&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]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31592&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31592&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'Herman Ole Andreas Wold' @ 193.190.124.10:1001






Variance Reduction Matrix
V(Y[t],d=0,D=0)208.714647160069Range75.3Trim Var.134.092950758978
V(Y[t],d=1,D=0)301.492512488980Range92.4Trim Var.164.084718417047
V(Y[t],d=2,D=0)746.622228244505Range130.8Trim Var.453.957697574335
V(Y[t],d=3,D=0)2195.84044444444Range241.2Trim Var.1262.85956539235
V(Y[t],d=0,D=1)57.7830907668232Range38.6Trim Var.31.6703149801587
V(Y[t],d=1,D=1)84.8091951710261Range48Trim Var.46.5367025089606
V(Y[t],d=2,D=1)266.191720496894Range81.4Trim Var.140.729360126917
V(Y[t],d=3,D=1)922.221935208866Range158Trim Var.516.436633879781
V(Y[t],d=0,D=2)140.147940677966Range53.3Trim Var.89.7215094339623
V(Y[t],d=1,D=2)211.078772647574Range73.1Trim Var.119.292728592163
V(Y[t],d=2,D=2)679.774579552329Range128.6Trim Var.369.103680241327
V(Y[t],d=3,D=2)2422.04280701754Range253.1Trim Var.1340.05819607843

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 208.714647160069 & Range & 75.3 & Trim Var. & 134.092950758978 \tabularnewline
V(Y[t],d=1,D=0) & 301.492512488980 & Range & 92.4 & Trim Var. & 164.084718417047 \tabularnewline
V(Y[t],d=2,D=0) & 746.622228244505 & Range & 130.8 & Trim Var. & 453.957697574335 \tabularnewline
V(Y[t],d=3,D=0) & 2195.84044444444 & Range & 241.2 & Trim Var. & 1262.85956539235 \tabularnewline
V(Y[t],d=0,D=1) & 57.7830907668232 & Range & 38.6 & Trim Var. & 31.6703149801587 \tabularnewline
V(Y[t],d=1,D=1) & 84.8091951710261 & Range & 48 & Trim Var. & 46.5367025089606 \tabularnewline
V(Y[t],d=2,D=1) & 266.191720496894 & Range & 81.4 & Trim Var. & 140.729360126917 \tabularnewline
V(Y[t],d=3,D=1) & 922.221935208866 & Range & 158 & Trim Var. & 516.436633879781 \tabularnewline
V(Y[t],d=0,D=2) & 140.147940677966 & Range & 53.3 & Trim Var. & 89.7215094339623 \tabularnewline
V(Y[t],d=1,D=2) & 211.078772647574 & Range & 73.1 & Trim Var. & 119.292728592163 \tabularnewline
V(Y[t],d=2,D=2) & 679.774579552329 & Range & 128.6 & Trim Var. & 369.103680241327 \tabularnewline
V(Y[t],d=3,D=2) & 2422.04280701754 & Range & 253.1 & Trim Var. & 1340.05819607843 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31592&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]208.714647160069[/C][C]Range[/C][C]75.3[/C][C]Trim Var.[/C][C]134.092950758978[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]301.492512488980[/C][C]Range[/C][C]92.4[/C][C]Trim Var.[/C][C]164.084718417047[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]746.622228244505[/C][C]Range[/C][C]130.8[/C][C]Trim Var.[/C][C]453.957697574335[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]2195.84044444444[/C][C]Range[/C][C]241.2[/C][C]Trim Var.[/C][C]1262.85956539235[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]57.7830907668232[/C][C]Range[/C][C]38.6[/C][C]Trim Var.[/C][C]31.6703149801587[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]84.8091951710261[/C][C]Range[/C][C]48[/C][C]Trim Var.[/C][C]46.5367025089606[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]266.191720496894[/C][C]Range[/C][C]81.4[/C][C]Trim Var.[/C][C]140.729360126917[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]922.221935208866[/C][C]Range[/C][C]158[/C][C]Trim Var.[/C][C]516.436633879781[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]140.147940677966[/C][C]Range[/C][C]53.3[/C][C]Trim Var.[/C][C]89.7215094339623[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]211.078772647574[/C][C]Range[/C][C]73.1[/C][C]Trim Var.[/C][C]119.292728592163[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]679.774579552329[/C][C]Range[/C][C]128.6[/C][C]Trim Var.[/C][C]369.103680241327[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]2422.04280701754[/C][C]Range[/C][C]253.1[/C][C]Trim Var.[/C][C]1340.05819607843[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31592&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31592&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)208.714647160069Range75.3Trim Var.134.092950758978
V(Y[t],d=1,D=0)301.492512488980Range92.4Trim Var.164.084718417047
V(Y[t],d=2,D=0)746.622228244505Range130.8Trim Var.453.957697574335
V(Y[t],d=3,D=0)2195.84044444444Range241.2Trim Var.1262.85956539235
V(Y[t],d=0,D=1)57.7830907668232Range38.6Trim Var.31.6703149801587
V(Y[t],d=1,D=1)84.8091951710261Range48Trim Var.46.5367025089606
V(Y[t],d=2,D=1)266.191720496894Range81.4Trim Var.140.729360126917
V(Y[t],d=3,D=1)922.221935208866Range158Trim Var.516.436633879781
V(Y[t],d=0,D=2)140.147940677966Range53.3Trim Var.89.7215094339623
V(Y[t],d=1,D=2)211.078772647574Range73.1Trim Var.119.292728592163
V(Y[t],d=2,D=2)679.774579552329Range128.6Trim Var.369.103680241327
V(Y[t],d=3,D=2)2422.04280701754Range253.1Trim Var.1340.05819607843


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')