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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 computationSun, 19 Dec 2010 14:36:42 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/19/t1292769758ulmf6byneqpfy3i.htm/, Retrieved Sun, 05 May 2024 07:18:07 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=112444, Retrieved Sun, 05 May 2024 07:18:07 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact165

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Variance Reduction Matrix] [Unemployment] [2010-11-29 09:29:57] [b98453cac15ba1066b407e146608df68]
-   PD  [Variance Reduction Matrix] [WS 9 Variance Red...] [2010-12-03 17:46:28] [8081b8996d5947580de3eb171e82db4f]
-    D    [Variance Reduction Matrix] [Workshop 9, VRM] [2010-12-05 18:42:47] [3635fb7041b1998c5a1332cf9de22bce]
- R  D        [Variance Reduction Matrix] [Paper VRM] [2010-12-19 14:36:42] [23a9b79f355c69a75648521a893cf584] [Current]
-    D          [Variance Reduction Matrix] [Paper VRM werklozen] [2010-12-19 16:11:31] [d946de7cca328fbcf207448a112523ab]
- RM D          [(Partial) Autocorrelation Function] [Paper VRM 2] [2010-12-19 20:40:03] [3635fb7041b1998c5a1332cf9de22bce]
-   P             [(Partial) Autocorrelation Function] [Variance Reductio...] [2010-12-22 08:43:47] [8081b8996d5947580de3eb171e82db4f]
-   P             [(Partial) Autocorrelation Function] [Paper Variance Re...] [2010-12-22 09:01:18] [d946de7cca328fbcf207448a112523ab]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
631 923
654 294
671 833
586 840
600 969
625 568
558 110
630 577
628 654
603 184
656 255
600 730
670 326
678 423
641 502
625 311
628 177
589 767
582 471
636 248
599 885
621 694
637 406
595 994
696 308
674 201
648 861
649 605
672 392
598 396
613 177
638 104
615 632
634 465
638 686
604 243
706 669
677 185
644 328
664 825
605 707
600 136
612 166
599 659
634 210
618 234
613 576
627 200
668 973
651 479
619 661
644 260
579 936
601 752
595 376
588 902
634 341
594 305
606 200
610 926
633 685
639 696
659 451
593 248
606 677
599 434
569 578
629 873
613 438
604 172
658 328
612 633
707 372
739 770
777 535
685 030
730 234
714 154
630 872
719 492
677 023
679 272
718 317
645 672

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 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 & 4 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112444&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]4 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=112444&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112444&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 time4 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Variance Reduction Matrix
V(Y[t],d=0,D=0)1730981949.46687Range219425Trim Var.974186101.001851
V(Y[t],d=1,D=0)1850213478.59594Range194931Trim Var.1049952950.78501
V(Y[t],d=2,D=0)5432417192.89009Range303812Trim Var.3558684456.76056
V(Y[t],d=3,D=0)17908734445.7568Range570970Trim Var.11667843835.2249
V(Y[t],d=0,D=1)1656960128.93818Range190242Trim Var.961705432.765625
V(Y[t],d=1,D=1)1415035870.87968Range168555Trim Var.897712461.504352
V(Y[t],d=2,D=1)4493897830.63023Range310930Trim Var.2762678001.26917
V(Y[t],d=3,D=1)15212243674.734Range586297Trim Var.9414143752.48306
V(Y[t],d=0,D=2)2240833802.38729Range253694Trim Var.1381341636.32704
V(Y[t],d=1,D=2)2183220785.14494Range205837Trim Var.1461264652.33745
V(Y[t],d=2,D=2)7103996836.25923Range351275Trim Var.4998358335.11727
V(Y[t],d=3,D=2)24293602419.9192Range657977Trim Var.16599937121.4729

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 1730981949.46687 & Range & 219425 & Trim Var. & 974186101.001851 \tabularnewline
V(Y[t],d=1,D=0) & 1850213478.59594 & Range & 194931 & Trim Var. & 1049952950.78501 \tabularnewline
V(Y[t],d=2,D=0) & 5432417192.89009 & Range & 303812 & Trim Var. & 3558684456.76056 \tabularnewline
V(Y[t],d=3,D=0) & 17908734445.7568 & Range & 570970 & Trim Var. & 11667843835.2249 \tabularnewline
V(Y[t],d=0,D=1) & 1656960128.93818 & Range & 190242 & Trim Var. & 961705432.765625 \tabularnewline
V(Y[t],d=1,D=1) & 1415035870.87968 & Range & 168555 & Trim Var. & 897712461.504352 \tabularnewline
V(Y[t],d=2,D=1) & 4493897830.63023 & Range & 310930 & Trim Var. & 2762678001.26917 \tabularnewline
V(Y[t],d=3,D=1) & 15212243674.734 & Range & 586297 & Trim Var. & 9414143752.48306 \tabularnewline
V(Y[t],d=0,D=2) & 2240833802.38729 & Range & 253694 & Trim Var. & 1381341636.32704 \tabularnewline
V(Y[t],d=1,D=2) & 2183220785.14494 & Range & 205837 & Trim Var. & 1461264652.33745 \tabularnewline
V(Y[t],d=2,D=2) & 7103996836.25923 & Range & 351275 & Trim Var. & 4998358335.11727 \tabularnewline
V(Y[t],d=3,D=2) & 24293602419.9192 & Range & 657977 & Trim Var. & 16599937121.4729 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112444&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]1730981949.46687[/C][C]Range[/C][C]219425[/C][C]Trim Var.[/C][C]974186101.001851[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]1850213478.59594[/C][C]Range[/C][C]194931[/C][C]Trim Var.[/C][C]1049952950.78501[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]5432417192.89009[/C][C]Range[/C][C]303812[/C][C]Trim Var.[/C][C]3558684456.76056[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]17908734445.7568[/C][C]Range[/C][C]570970[/C][C]Trim Var.[/C][C]11667843835.2249[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]1656960128.93818[/C][C]Range[/C][C]190242[/C][C]Trim Var.[/C][C]961705432.765625[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]1415035870.87968[/C][C]Range[/C][C]168555[/C][C]Trim Var.[/C][C]897712461.504352[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]4493897830.63023[/C][C]Range[/C][C]310930[/C][C]Trim Var.[/C][C]2762678001.26917[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]15212243674.734[/C][C]Range[/C][C]586297[/C][C]Trim Var.[/C][C]9414143752.48306[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]2240833802.38729[/C][C]Range[/C][C]253694[/C][C]Trim Var.[/C][C]1381341636.32704[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]2183220785.14494[/C][C]Range[/C][C]205837[/C][C]Trim Var.[/C][C]1461264652.33745[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]7103996836.25923[/C][C]Range[/C][C]351275[/C][C]Trim Var.[/C][C]4998358335.11727[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]24293602419.9192[/C][C]Range[/C][C]657977[/C][C]Trim Var.[/C][C]16599937121.4729[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112444&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112444&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)1730981949.46687Range219425Trim Var.974186101.001851
V(Y[t],d=1,D=0)1850213478.59594Range194931Trim Var.1049952950.78501
V(Y[t],d=2,D=0)5432417192.89009Range303812Trim Var.3558684456.76056
V(Y[t],d=3,D=0)17908734445.7568Range570970Trim Var.11667843835.2249
V(Y[t],d=0,D=1)1656960128.93818Range190242Trim Var.961705432.765625
V(Y[t],d=1,D=1)1415035870.87968Range168555Trim Var.897712461.504352
V(Y[t],d=2,D=1)4493897830.63023Range310930Trim Var.2762678001.26917
V(Y[t],d=3,D=1)15212243674.734Range586297Trim Var.9414143752.48306
V(Y[t],d=0,D=2)2240833802.38729Range253694Trim Var.1381341636.32704
V(Y[t],d=1,D=2)2183220785.14494Range205837Trim Var.1461264652.33745
V(Y[t],d=2,D=2)7103996836.25923Range351275Trim Var.4998358335.11727
V(Y[t],d=3,D=2)24293602419.9192Range657977Trim Var.16599937121.4729


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(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()