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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, 02 Dec 2008 12:39:59 -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/02/t1228246847udbo1fih9hc402h.htm/, Retrieved Fri, 17 May 2024 05:14:37 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=28262, Retrieved Fri, 17 May 2024 05:14:37 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsnon stationary time series , Q8
Estimated Impact162

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Data Series] [Airline data] [2007-10-18 09:58:47] [42daae401fd3def69a25014f2252b4c2]
F RMPD  [Cross Correlation Function] [loïqueverhasselt] [2008-12-02 18:09:48] [0e879b146665902680dd148a904a2646]
F   PD    [Cross Correlation Function] [loïqueverhasselt] [2008-12-02 18:24:22] [0e879b146665902680dd148a904a2646]
F RMPD      [Variance Reduction Matrix] [loïqueverhasselt] [2008-12-02 19:35:00] [0e879b146665902680dd148a904a2646]
F    D          [Variance Reduction Matrix] [loïqueverhasselt] [2008-12-02 19:39:59] [6440ec5a21e5d35520cb2ae6b4b70e45] [Current]
Feedback Forum
2008-12-07 09:49:50 [Gert-Jan Geudens] [reply] 
De student(e) heeft correcte berekeningen gemaakt en heeft het correcte resultaat gevonden.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
99.4
97.5
94.6
92.6
92.5
89.8
88.8
87.4
85.2
83.1
84.7
84.8
85.8
86.3
89
89
89.3
91.9
94.9
94.4
96.8
96.9
98
97.9
100.9
103.9
103.1
102.5
104.3
102.6
101.7
102.8
105.4
110.9
113.5
116.3
124
128.8
133.5
132.6
128.4
127.3
126.7
123.3
123.2
124.4
128.2
128.7
135.7
139
145.4
142.4
137.7
137
137.1
139.3
139.6
140.4
142.3
148.3

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=28262&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=28262&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28262&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)413.261344632768Range65.2Trim Var.352.177166317261
V(Y[t],d=1,D=0)7.54691408533022Range12.4000000000000Trim Var.4.75711901306241
V(Y[t],d=2,D=0)8.1763853599516Range15.9Trim Var.4.85269984917044
V(Y[t],d=3,D=0)21.5438157894737Range22.3Trim Var.13.6341254901961
V(Y[t],d=0,D=1)84.634024822695Range44Trim Var.39.2145470383275
V(Y[t],d=1,D=1)8.94800185013877Range11.6Trim Var.5.65279487179487
V(Y[t],d=2,D=1)13.2960241545894Range13.4Trim Var.8.84094466936573
V(Y[t],d=3,D=1)36.2410909090909Range22.4000000000000Trim Var.26.5794466936572
V(Y[t],d=0,D=2)163.483325396825Range49.1Trim Var.109.530604838710
V(Y[t],d=1,D=2)26.9094957983193Range19.8Trim Var.18.1411612903225
V(Y[t],d=2,D=2)45.2880659536541Range23.1Trim Var.34.5561379310344
V(Y[t],d=3,D=2)128.334602272727Range38.6Trim Var.98.6773891625612

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 413.261344632768 & Range & 65.2 & Trim Var. & 352.177166317261 \tabularnewline
V(Y[t],d=1,D=0) & 7.54691408533022 & Range & 12.4000000000000 & Trim Var. & 4.75711901306241 \tabularnewline
V(Y[t],d=2,D=0) & 8.1763853599516 & Range & 15.9 & Trim Var. & 4.85269984917044 \tabularnewline
V(Y[t],d=3,D=0) & 21.5438157894737 & Range & 22.3 & Trim Var. & 13.6341254901961 \tabularnewline
V(Y[t],d=0,D=1) & 84.634024822695 & Range & 44 & Trim Var. & 39.2145470383275 \tabularnewline
V(Y[t],d=1,D=1) & 8.94800185013877 & Range & 11.6 & Trim Var. & 5.65279487179487 \tabularnewline
V(Y[t],d=2,D=1) & 13.2960241545894 & Range & 13.4 & Trim Var. & 8.84094466936573 \tabularnewline
V(Y[t],d=3,D=1) & 36.2410909090909 & Range & 22.4000000000000 & Trim Var. & 26.5794466936572 \tabularnewline
V(Y[t],d=0,D=2) & 163.483325396825 & Range & 49.1 & Trim Var. & 109.530604838710 \tabularnewline
V(Y[t],d=1,D=2) & 26.9094957983193 & Range & 19.8 & Trim Var. & 18.1411612903225 \tabularnewline
V(Y[t],d=2,D=2) & 45.2880659536541 & Range & 23.1 & Trim Var. & 34.5561379310344 \tabularnewline
V(Y[t],d=3,D=2) & 128.334602272727 & Range & 38.6 & Trim Var. & 98.6773891625612 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28262&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]413.261344632768[/C][C]Range[/C][C]65.2[/C][C]Trim Var.[/C][C]352.177166317261[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]7.54691408533022[/C][C]Range[/C][C]12.4000000000000[/C][C]Trim Var.[/C][C]4.75711901306241[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]8.1763853599516[/C][C]Range[/C][C]15.9[/C][C]Trim Var.[/C][C]4.85269984917044[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]21.5438157894737[/C][C]Range[/C][C]22.3[/C][C]Trim Var.[/C][C]13.6341254901961[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]84.634024822695[/C][C]Range[/C][C]44[/C][C]Trim Var.[/C][C]39.2145470383275[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]8.94800185013877[/C][C]Range[/C][C]11.6[/C][C]Trim Var.[/C][C]5.65279487179487[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]13.2960241545894[/C][C]Range[/C][C]13.4[/C][C]Trim Var.[/C][C]8.84094466936573[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]36.2410909090909[/C][C]Range[/C][C]22.4000000000000[/C][C]Trim Var.[/C][C]26.5794466936572[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]163.483325396825[/C][C]Range[/C][C]49.1[/C][C]Trim Var.[/C][C]109.530604838710[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]26.9094957983193[/C][C]Range[/C][C]19.8[/C][C]Trim Var.[/C][C]18.1411612903225[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]45.2880659536541[/C][C]Range[/C][C]23.1[/C][C]Trim Var.[/C][C]34.5561379310344[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]128.334602272727[/C][C]Range[/C][C]38.6[/C][C]Trim Var.[/C][C]98.6773891625612[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28262&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28262&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)413.261344632768Range65.2Trim Var.352.177166317261
V(Y[t],d=1,D=0)7.54691408533022Range12.4000000000000Trim Var.4.75711901306241
V(Y[t],d=2,D=0)8.1763853599516Range15.9Trim Var.4.85269984917044
V(Y[t],d=3,D=0)21.5438157894737Range22.3Trim Var.13.6341254901961
V(Y[t],d=0,D=1)84.634024822695Range44Trim Var.39.2145470383275
V(Y[t],d=1,D=1)8.94800185013877Range11.6Trim Var.5.65279487179487
V(Y[t],d=2,D=1)13.2960241545894Range13.4Trim Var.8.84094466936573
V(Y[t],d=3,D=1)36.2410909090909Range22.4000000000000Trim Var.26.5794466936572
V(Y[t],d=0,D=2)163.483325396825Range49.1Trim Var.109.530604838710
V(Y[t],d=1,D=2)26.9094957983193Range19.8Trim Var.18.1411612903225
V(Y[t],d=2,D=2)45.2880659536541Range23.1Trim Var.34.5561379310344
V(Y[t],d=3,D=2)128.334602272727Range38.6Trim Var.98.6773891625612


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')