Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_variancereduction.wasp
Title produced by softwareVariance Reduction Matrix
Date of computationSat, 06 Dec 2008 04:59:34 -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/06/t12285648301xkm3ecq46z0p3a.htm/, Retrieved Thu, 31 Oct 2024 22:56:24 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=29529, Retrieved Thu, 31 Oct 2024 22:56:24 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact245
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] [question 8] [2008-12-02 14:53:11] [31c9f333c18b3396ccf9d2485dd39c8a]
- RMPD      [Variance Reduction Matrix] [] [2008-12-06 11:59:34] [86e877ba38171644c8ca01af8044e645] [Current]
Feedback Forum

Post a new message
Dataseries X:
123.28
133.52
153.20
163.63
168.45
166.26
162.31
161.56
156.59
157.97
158.68
163.55
162.89
164.95
159.82
159.05
166.76
164.55
163.22
160.68
155.24
157.60
156.56
154.82
151.11
149.65
148.99
148.53
146.70
145.11
142.70
143.59
140.96
140.77
139.81
140.58
139.59
138.05
136.06
135.98
134.75
132.22
135.37
138.84
138.83
136.55
135.63
139.14
136.09
135.97
134.51
134.54
134.08
132.86
134.48
129.08
133.13
134.78
134.13
132.43
127.84
128.12
128.94
132.38
134.99
138.05
135.83
130.12
128.16
128.60
126.12
124.20
121.65
121.57
118.38
116.31
117.11
117.80
115.86
115.81
114.75
116.23
117.12
113.38
108.68
109.86
108.20
109.34
107.21
104.30
106.50
110.36
110.33
107.08
109.57
100.61
93.26
92.74
93.11
97.76
101.39
100.71
98.09
99.92
102.59
107.64
106.53
103.72
108.25
113.52
112.39
120.10
123.71
125.32
129.71
128.16
130.20
130.78
131.35




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 0 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29529&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]0 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29529&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29529&T=0

As an alternative you can also use a 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 time0 seconds
R Server'George Udny Yule' @ 72.249.76.132







Variance Reduction Matrix
V(Y[t],d=0,D=0)386.658115624555Range75.71Trim Var.291.322675630400
V(Y[t],d=1,D=0)13.6286238809213Range28.64Trim Var.5.65142109613656
V(Y[t],d=2,D=0)16.5035265399351Range20.8999999999999Trim Var.9.67336543956043
V(Y[t],d=3,D=0)44.3970021814092Range35.1599999999999Trim Var.25.7383073935773
V(Y[t],d=0,D=1)158.836639252336Range60.13Trim Var.84.72349462486
V(Y[t],d=1,D=1)19.8693112039532Range36.69Trim Var.7.55287441088994
V(Y[t],d=2,D=1)26.6234471062270Range30.7199999999999Trim Var.13.1892086489013
V(Y[t],d=3,D=1)65.9953874159819Range47.7399999999999Trim Var.32.6822244027710
V(Y[t],d=0,D=2)256.168852698768Range91.42Trim Var.128.192558543417
V(Y[t],d=1,D=2)40.9985075840768Range42.0500000000000Trim Var.20.517764242685
V(Y[t],d=2,D=2)67.2653507246375Range48.5599999999999Trim Var.34.8408344401998
V(Y[t],d=3,D=2)165.510783695652Range79.3999999999999Trim Var.75.7432781240587

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 386.658115624555 & Range & 75.71 & Trim Var. & 291.322675630400 \tabularnewline
V(Y[t],d=1,D=0) & 13.6286238809213 & Range & 28.64 & Trim Var. & 5.65142109613656 \tabularnewline
V(Y[t],d=2,D=0) & 16.5035265399351 & Range & 20.8999999999999 & Trim Var. & 9.67336543956043 \tabularnewline
V(Y[t],d=3,D=0) & 44.3970021814092 & Range & 35.1599999999999 & Trim Var. & 25.7383073935773 \tabularnewline
V(Y[t],d=0,D=1) & 158.836639252336 & Range & 60.13 & Trim Var. & 84.72349462486 \tabularnewline
V(Y[t],d=1,D=1) & 19.8693112039532 & Range & 36.69 & Trim Var. & 7.55287441088994 \tabularnewline
V(Y[t],d=2,D=1) & 26.6234471062270 & Range & 30.7199999999999 & Trim Var. & 13.1892086489013 \tabularnewline
V(Y[t],d=3,D=1) & 65.9953874159819 & Range & 47.7399999999999 & Trim Var. & 32.6822244027710 \tabularnewline
V(Y[t],d=0,D=2) & 256.168852698768 & Range & 91.42 & Trim Var. & 128.192558543417 \tabularnewline
V(Y[t],d=1,D=2) & 40.9985075840768 & Range & 42.0500000000000 & Trim Var. & 20.517764242685 \tabularnewline
V(Y[t],d=2,D=2) & 67.2653507246375 & Range & 48.5599999999999 & Trim Var. & 34.8408344401998 \tabularnewline
V(Y[t],d=3,D=2) & 165.510783695652 & Range & 79.3999999999999 & Trim Var. & 75.7432781240587 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29529&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]386.658115624555[/C][C]Range[/C][C]75.71[/C][C]Trim Var.[/C][C]291.322675630400[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]13.6286238809213[/C][C]Range[/C][C]28.64[/C][C]Trim Var.[/C][C]5.65142109613656[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]16.5035265399351[/C][C]Range[/C][C]20.8999999999999[/C][C]Trim Var.[/C][C]9.67336543956043[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]44.3970021814092[/C][C]Range[/C][C]35.1599999999999[/C][C]Trim Var.[/C][C]25.7383073935773[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]158.836639252336[/C][C]Range[/C][C]60.13[/C][C]Trim Var.[/C][C]84.72349462486[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]19.8693112039532[/C][C]Range[/C][C]36.69[/C][C]Trim Var.[/C][C]7.55287441088994[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]26.6234471062270[/C][C]Range[/C][C]30.7199999999999[/C][C]Trim Var.[/C][C]13.1892086489013[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]65.9953874159819[/C][C]Range[/C][C]47.7399999999999[/C][C]Trim Var.[/C][C]32.6822244027710[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]256.168852698768[/C][C]Range[/C][C]91.42[/C][C]Trim Var.[/C][C]128.192558543417[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]40.9985075840768[/C][C]Range[/C][C]42.0500000000000[/C][C]Trim Var.[/C][C]20.517764242685[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]67.2653507246375[/C][C]Range[/C][C]48.5599999999999[/C][C]Trim Var.[/C][C]34.8408344401998[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]165.510783695652[/C][C]Range[/C][C]79.3999999999999[/C][C]Trim Var.[/C][C]75.7432781240587[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29529&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29529&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Variance Reduction Matrix
V(Y[t],d=0,D=0)386.658115624555Range75.71Trim Var.291.322675630400
V(Y[t],d=1,D=0)13.6286238809213Range28.64Trim Var.5.65142109613656
V(Y[t],d=2,D=0)16.5035265399351Range20.8999999999999Trim Var.9.67336543956043
V(Y[t],d=3,D=0)44.3970021814092Range35.1599999999999Trim Var.25.7383073935773
V(Y[t],d=0,D=1)158.836639252336Range60.13Trim Var.84.72349462486
V(Y[t],d=1,D=1)19.8693112039532Range36.69Trim Var.7.55287441088994
V(Y[t],d=2,D=1)26.6234471062270Range30.7199999999999Trim Var.13.1892086489013
V(Y[t],d=3,D=1)65.9953874159819Range47.7399999999999Trim Var.32.6822244027710
V(Y[t],d=0,D=2)256.168852698768Range91.42Trim Var.128.192558543417
V(Y[t],d=1,D=2)40.9985075840768Range42.0500000000000Trim Var.20.517764242685
V(Y[t],d=2,D=2)67.2653507246375Range48.5599999999999Trim Var.34.8408344401998
V(Y[t],d=3,D=2)165.510783695652Range79.3999999999999Trim Var.75.7432781240587



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')