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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 computationThu, 09 Dec 2010 20:10:17 +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/09/t1291925356on3hjhm13ypz63w.htm/, Retrieved Mon, 29 Apr 2024 06:36:54 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=107382, Retrieved Mon, 29 Apr 2024 06:36:54 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsPaper DMA
Estimated Impact172

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Data Series] [Bivariate dataset] [2008-01-05 23:51:08] [74be16979710d4c4e7c6647856088456]
- RMPD  [Bivariate Explorative Data Analysis] [Ws4 part 1.1 s090...] [2009-10-27 21:56:53] [e0fc65a5811681d807296d590d5b45de]
-  M D    [Bivariate Explorative Data Analysis] [Paper; bivariate ...] [2009-12-19 19:10:37] [e0fc65a5811681d807296d590d5b45de]
- RMPD      [Cross Correlation Function] [cross correlation...] [2010-12-08 19:50:23] [74be16979710d4c4e7c6647856088456]
-   PD        [Cross Correlation Function] [] [2010-12-09 09:25:48] [b98453cac15ba1066b407e146608df68]
- RMPD            [Variance Reduction Matrix] [PAPER DMA VRM Olie] [2010-12-09 20:10:17] [f92ba2b01007f169e2985fcc57236bd0] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
25,64
27,97
27,62
23,31
29,07
29,58
28,63
29,92
32,68
31,54
32,43
26,54
25,85
27,6
25,71
25,38
28,57
27,64
25,36
25,9
26,29
21,74
19,2
19,32
19,82
20,36
24,31
25,97
25,61
24,67
25,59
26,09
28,37
27,34
24,46
27,46
30,23
32,33
29,87
24,87
25,48
27,28
28,24
29,58
26,95
29,08
28,76
29,59
30,7
30,52
32,67
33,19
37,13
35,54
37,75
41,84
42,94
49,14
44,61
40,22
44,23
45,85
53,38
53,26
51,8
55,3
57,81
63,96
63,77
59,15
56,12
57,42
63,52
61,71
63,01
68,18
72,03
69,75
74,41
74,33
64,24
60,03
59,44
62,5
55,04
58,34
61,92
67,65
67,68
70,3
75,26
71,44
76,36
81,71
92,6
90,6
92,23
94,09
102,79
109,65
124,05
132,69
135,81
116,07
101,42
75,73
55,48
43,8
45,29

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=107382&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=107382&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=107382&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 time1 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk






Variance Reduction Matrix
V(Y[t],d=0,D=0)716.98711751614Range116.61Trim Var.421.079782646048
V(Y[t],d=1,D=0)31.3727578660436Range40.09Trim Var.8.6758247258772
V(Y[t],d=2,D=0)30.0409132604479Range36.03Trim Var.15.2497778275476
V(Y[t],d=3,D=0)74.82661787062Range46.38Trim Var.42.3065896247998
V(Y[t],d=0,D=1)308.612833140034Range109.33Trim Var.119.12173223737
V(Y[t],d=1,D=1)50.3889639364035Range46.15Trim Var.15.5149535567716
V(Y[t],d=2,D=1)51.8476400223964Range38Trim Var.28.2487430812325
V(Y[t],d=3,D=1)131.183779867307Range58.67Trim Var.74.425991551922
V(Y[t],d=0,D=2)580.831791316527Range145.97Trim Var.189.420050702703
V(Y[t],d=1,D=2)114.939771930579Range67.53Trim Var.37.5532534801925
V(Y[t],d=2,D=2)139.292616044667Range67.2Trim Var.72.4484048706241
V(Y[t],d=3,D=2)371.785927792834Range104Trim Var.190.707333959312

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 716.98711751614 & Range & 116.61 & Trim Var. & 421.079782646048 \tabularnewline
V(Y[t],d=1,D=0) & 31.3727578660436 & Range & 40.09 & Trim Var. & 8.6758247258772 \tabularnewline
V(Y[t],d=2,D=0) & 30.0409132604479 & Range & 36.03 & Trim Var. & 15.2497778275476 \tabularnewline
V(Y[t],d=3,D=0) & 74.82661787062 & Range & 46.38 & Trim Var. & 42.3065896247998 \tabularnewline
V(Y[t],d=0,D=1) & 308.612833140034 & Range & 109.33 & Trim Var. & 119.12173223737 \tabularnewline
V(Y[t],d=1,D=1) & 50.3889639364035 & Range & 46.15 & Trim Var. & 15.5149535567716 \tabularnewline
V(Y[t],d=2,D=1) & 51.8476400223964 & Range & 38 & Trim Var. & 28.2487430812325 \tabularnewline
V(Y[t],d=3,D=1) & 131.183779867307 & Range & 58.67 & Trim Var. & 74.425991551922 \tabularnewline
V(Y[t],d=0,D=2) & 580.831791316527 & Range & 145.97 & Trim Var. & 189.420050702703 \tabularnewline
V(Y[t],d=1,D=2) & 114.939771930579 & Range & 67.53 & Trim Var. & 37.5532534801925 \tabularnewline
V(Y[t],d=2,D=2) & 139.292616044667 & Range & 67.2 & Trim Var. & 72.4484048706241 \tabularnewline
V(Y[t],d=3,D=2) & 371.785927792834 & Range & 104 & Trim Var. & 190.707333959312 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=107382&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]716.98711751614[/C][C]Range[/C][C]116.61[/C][C]Trim Var.[/C][C]421.079782646048[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]31.3727578660436[/C][C]Range[/C][C]40.09[/C][C]Trim Var.[/C][C]8.6758247258772[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]30.0409132604479[/C][C]Range[/C][C]36.03[/C][C]Trim Var.[/C][C]15.2497778275476[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]74.82661787062[/C][C]Range[/C][C]46.38[/C][C]Trim Var.[/C][C]42.3065896247998[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]308.612833140034[/C][C]Range[/C][C]109.33[/C][C]Trim Var.[/C][C]119.12173223737[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]50.3889639364035[/C][C]Range[/C][C]46.15[/C][C]Trim Var.[/C][C]15.5149535567716[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]51.8476400223964[/C][C]Range[/C][C]38[/C][C]Trim Var.[/C][C]28.2487430812325[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]131.183779867307[/C][C]Range[/C][C]58.67[/C][C]Trim Var.[/C][C]74.425991551922[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]580.831791316527[/C][C]Range[/C][C]145.97[/C][C]Trim Var.[/C][C]189.420050702703[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]114.939771930579[/C][C]Range[/C][C]67.53[/C][C]Trim Var.[/C][C]37.5532534801925[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]139.292616044667[/C][C]Range[/C][C]67.2[/C][C]Trim Var.[/C][C]72.4484048706241[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]371.785927792834[/C][C]Range[/C][C]104[/C][C]Trim Var.[/C][C]190.707333959312[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=107382&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=107382&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)716.98711751614Range116.61Trim Var.421.079782646048
V(Y[t],d=1,D=0)31.3727578660436Range40.09Trim Var.8.6758247258772
V(Y[t],d=2,D=0)30.0409132604479Range36.03Trim Var.15.2497778275476
V(Y[t],d=3,D=0)74.82661787062Range46.38Trim Var.42.3065896247998
V(Y[t],d=0,D=1)308.612833140034Range109.33Trim Var.119.12173223737
V(Y[t],d=1,D=1)50.3889639364035Range46.15Trim Var.15.5149535567716
V(Y[t],d=2,D=1)51.8476400223964Range38Trim Var.28.2487430812325
V(Y[t],d=3,D=1)131.183779867307Range58.67Trim Var.74.425991551922
V(Y[t],d=0,D=2)580.831791316527Range145.97Trim Var.189.420050702703
V(Y[t],d=1,D=2)114.939771930579Range67.53Trim Var.37.5532534801925
V(Y[t],d=2,D=2)139.292616044667Range67.2Trim Var.72.4484048706241
V(Y[t],d=3,D=2)371.785927792834Range104Trim Var.190.707333959312


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ;
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')