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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 computationMon, 03 Dec 2012 15:17:14 -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/2012/Dec/03/t13545658801aa4dtitoyg2d4y.htm/, Retrieved Sun, 05 May 2024 06:40:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=196011, Retrieved Sun, 05 May 2024 06:40:58 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact96
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [(Partial) Autocorrelation Function] [Workshop 9 - auto...] [2012-12-03 19:55:49] [c85dbc843174c8f40de92b1c92b5205a]
- R P   [(Partial) Autocorrelation Function] [Workshop 9 - auto...] [2012-12-03 19:57:39] [c85dbc843174c8f40de92b1c92b5205a]
- RMP     [Spectral Analysis] [Workshop 9 - peri...] [2012-12-03 20:02:49] [c85dbc843174c8f40de92b1c92b5205a]
- R P       [Spectral Analysis] [Workshop 9 - peri...] [2012-12-03 20:04:57] [c85dbc843174c8f40de92b1c92b5205a]
- RMP           [Variance Reduction Matrix] [Workshop 9 - vari...] [2012-12-03 20:17:14] [729cfeb7382ca95684eaaf6b24800101] [Current]
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Dataseries X:
178421
139871
118159
109763
97415
119190
97903
96953
87888
84637
90549
95680
99371
79984
86752
85733
84906
78356
108895
101768
73285
65724
67457
67203
69273
80807
75129
74991
68157
73858
71349
85634
91624
116014
120033
108651
105378
138939
132974
135277
152741
158417
157460
193997
154089
147570
162924
153629
155907
197675
250708
266652
209842
165826
137152
150581
145973
126532
115437
119526
110856
97243
103876
116370
109616
98365
90440
88899
92358
88394
98219
113546
107168
77540
74944
75641
75910
87384
84615
80420
80784
79933
82118
91420
112426
114528
131025
116460
111258
155318
155078
134794
139985
198778
172436
169585
203702
282392
220658
194472
269246
215340
218319
195724
174614
172085
152347
189615
173804
145683
133550
121156
112040
120767
127019
136295
113425
107815
100298
97048
98750
98235
101254
139589
134921
80355
80396
82183
79709
90781




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'George Udny Yule' @ yule.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 & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=196011&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=196011&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=196011&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 time1 seconds
R Server'George Udny Yule' @ yule.wessa.net







Variance Reduction Matrix
V(Y[t],d=0,D=0)2138366492.2638Range216668Trim Var.1244129898.11057
V(Y[t],d=1,D=0)490565783.049903Range140424Trim Var.189163525.173608
V(Y[t],d=2,D=0)1020748887.67101Range241384Trim Var.373769916.195622
V(Y[t],d=3,D=0)2873241039.39058Range415205Trim Var.911227840.69469
V(Y[t],d=0,D=1)1364920160.97175Range229094Trim Var.659588386.813063
V(Y[t],d=1,D=1)941164465.427484Range198234Trim Var.384120176.267977
V(Y[t],d=2,D=1)1944526478.76495Range370562Trim Var.737864429.426605
V(Y[t],d=3,D=1)5700240708.31081Range628993Trim Var.1658190259.02956
V(Y[t],d=0,D=2)3006572888.54823Range382485Trim Var.1110439438.09727
V(Y[t],d=1,D=2)2844142648.91033Range336466Trim Var.1267700080.72915
V(Y[t],d=2,D=2)5775190101.29972Range591917Trim Var.2127983897.14252
V(Y[t],d=3,D=2)17010578962.1241Range1075898Trim Var.5130913989.80674

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 2138366492.2638 & Range & 216668 & Trim Var. & 1244129898.11057 \tabularnewline
V(Y[t],d=1,D=0) & 490565783.049903 & Range & 140424 & Trim Var. & 189163525.173608 \tabularnewline
V(Y[t],d=2,D=0) & 1020748887.67101 & Range & 241384 & Trim Var. & 373769916.195622 \tabularnewline
V(Y[t],d=3,D=0) & 2873241039.39058 & Range & 415205 & Trim Var. & 911227840.69469 \tabularnewline
V(Y[t],d=0,D=1) & 1364920160.97175 & Range & 229094 & Trim Var. & 659588386.813063 \tabularnewline
V(Y[t],d=1,D=1) & 941164465.427484 & Range & 198234 & Trim Var. & 384120176.267977 \tabularnewline
V(Y[t],d=2,D=1) & 1944526478.76495 & Range & 370562 & Trim Var. & 737864429.426605 \tabularnewline
V(Y[t],d=3,D=1) & 5700240708.31081 & Range & 628993 & Trim Var. & 1658190259.02956 \tabularnewline
V(Y[t],d=0,D=2) & 3006572888.54823 & Range & 382485 & Trim Var. & 1110439438.09727 \tabularnewline
V(Y[t],d=1,D=2) & 2844142648.91033 & Range & 336466 & Trim Var. & 1267700080.72915 \tabularnewline
V(Y[t],d=2,D=2) & 5775190101.29972 & Range & 591917 & Trim Var. & 2127983897.14252 \tabularnewline
V(Y[t],d=3,D=2) & 17010578962.1241 & Range & 1075898 & Trim Var. & 5130913989.80674 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=196011&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]2138366492.2638[/C][C]Range[/C][C]216668[/C][C]Trim Var.[/C][C]1244129898.11057[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]490565783.049903[/C][C]Range[/C][C]140424[/C][C]Trim Var.[/C][C]189163525.173608[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]1020748887.67101[/C][C]Range[/C][C]241384[/C][C]Trim Var.[/C][C]373769916.195622[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]2873241039.39058[/C][C]Range[/C][C]415205[/C][C]Trim Var.[/C][C]911227840.69469[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]1364920160.97175[/C][C]Range[/C][C]229094[/C][C]Trim Var.[/C][C]659588386.813063[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]941164465.427484[/C][C]Range[/C][C]198234[/C][C]Trim Var.[/C][C]384120176.267977[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]1944526478.76495[/C][C]Range[/C][C]370562[/C][C]Trim Var.[/C][C]737864429.426605[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]5700240708.31081[/C][C]Range[/C][C]628993[/C][C]Trim Var.[/C][C]1658190259.02956[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]3006572888.54823[/C][C]Range[/C][C]382485[/C][C]Trim Var.[/C][C]1110439438.09727[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]2844142648.91033[/C][C]Range[/C][C]336466[/C][C]Trim Var.[/C][C]1267700080.72915[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]5775190101.29972[/C][C]Range[/C][C]591917[/C][C]Trim Var.[/C][C]2127983897.14252[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]17010578962.1241[/C][C]Range[/C][C]1075898[/C][C]Trim Var.[/C][C]5130913989.80674[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=196011&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=196011&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)2138366492.2638Range216668Trim Var.1244129898.11057
V(Y[t],d=1,D=0)490565783.049903Range140424Trim Var.189163525.173608
V(Y[t],d=2,D=0)1020748887.67101Range241384Trim Var.373769916.195622
V(Y[t],d=3,D=0)2873241039.39058Range415205Trim Var.911227840.69469
V(Y[t],d=0,D=1)1364920160.97175Range229094Trim Var.659588386.813063
V(Y[t],d=1,D=1)941164465.427484Range198234Trim Var.384120176.267977
V(Y[t],d=2,D=1)1944526478.76495Range370562Trim Var.737864429.426605
V(Y[t],d=3,D=1)5700240708.31081Range628993Trim Var.1658190259.02956
V(Y[t],d=0,D=2)3006572888.54823Range382485Trim Var.1110439438.09727
V(Y[t],d=1,D=2)2844142648.91033Range336466Trim Var.1267700080.72915
V(Y[t],d=2,D=2)5775190101.29972Range591917Trim Var.2127983897.14252
V(Y[t],d=3,D=2)17010578962.1241Range1075898Trim Var.5130913989.80674



Parameters (Session):
par1 = 4 ;
Parameters (R input):
par1 = 4 ;
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(myx,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')
bitmap(file='pic0.png')
op <- par(mfrow=c(2,2))
plot(x,type='l',xlab='time',ylab='value',main='d=0, D=0')
plot(diff(x,lag=1,differences=1),type='l',xlab='time',ylab='value',main='d=1, D=0')
plot(diff(x,lag=par1,differences=1),type='l',xlab='time',ylab='value',main='d=0, D=1')
plot(diff(diff(x,lag=1,differences=1),lag=par1,differences=1),type='l',xlab='time',ylab='value',main='d=1, D=1')
par(op)
dev.off()