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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 computationFri, 12 Dec 2008 02:38:10 -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/12/t1229074771hge9ks0xpmgeilm.htm/, Retrieved Fri, 17 May 2024 17:09:25 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=32502, Retrieved Fri, 17 May 2024 17:09:25 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact240

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [Run sequence plot...] [2008-12-02 21:55:47] [ed2ba3b6182103c15c0ab511ae4e6284]
- RMP     [Variance Reduction Matrix] [Variance reductio...] [2008-12-12 09:38:10] [a8228479d4547a92e2d3f176a5299609] [Current]
- RM        [Standard Deviation-Mean Plot] [Standard deviatio...] [2008-12-12 09:46:43] [ed2ba3b6182103c15c0ab511ae4e6284]
- RMP         [(Partial) Autocorrelation Function] [(P)ACF tabaksprod...] [2008-12-12 10:09:30] [ed2ba3b6182103c15c0ab511ae4e6284]
-   P           [(Partial) Autocorrelation Function] [] [2008-12-12 10:26:36] [ed2ba3b6182103c15c0ab511ae4e6284]
-                 [(Partial) Autocorrelation Function] [(P)ACF tabakspodu...] [2008-12-12 11:01:48] [ed2ba3b6182103c15c0ab511ae4e6284]
-   P               [(Partial) Autocorrelation Function] [(P)ACF tabaksprod...] [2008-12-13 12:52:28] [ed2ba3b6182103c15c0ab511ae4e6284]
- RMP           [Spectral Analysis] [Spectrale analyse...] [2008-12-12 10:30:46] [ed2ba3b6182103c15c0ab511ae4e6284]
-                 [Spectral Analysis] [Spectrale analyse...] [2008-12-12 11:05:23] [ed2ba3b6182103c15c0ab511ae4e6284]
- RMP               [ARIMA Backward Selection] [ARIMA backward se...] [2008-12-12 12:52:16] [ed2ba3b6182103c15c0ab511ae4e6284]
- RMPD                [ARIMA Forecasting] [] [2008-12-12 14:09:09] [a4ee3bef49b119f4bd2e925060c84f5e]
-   PD                [ARIMA Backward Selection] [] [2008-12-12 14:08:29] [a4ee3bef49b119f4bd2e925060c84f5e]
- RMP                 [(Partial) Autocorrelation Function] [] [2008-12-12 14:06:36] [a4ee3bef49b119f4bd2e925060c84f5e]
-   PD                [ARIMA Backward Selection] [] [2008-12-12 17:29:27] [a4ee3bef49b119f4bd2e925060c84f5e]
- RMPD                [ARIMA Forecasting] [] [2008-12-12 17:26:53] [a4ee3bef49b119f4bd2e925060c84f5e]
- RMP               [ARIMA Backward Selection] [ARIMA blog] [2008-12-12 13:09:51] [ed2ba3b6182103c15c0ab511ae4e6284]
-   P               [Spectral Analysis] [Spectrale analyse...] [2008-12-13 13:07:40] [ed2ba3b6182103c15c0ab511ae4e6284]
- RM        [ARIMA Backward Selection] [ARIMA backward se...] [2008-12-13 13:21:17] [ed2ba3b6182103c15c0ab511ae4e6284]
- RM          [ARIMA Forecasting] [ARIMA forecast Ta...] [2008-12-13 13:41:26] [ed2ba3b6182103c15c0ab511ae4e6284]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
44.9
48.1
52.3
48.9
52.6
60.3
50.5
41.6
56
51.4
52.9
54.9
43.9
51
51.9
54.3
50.3
57.2
48.8
41.1
58
63
53.8
54.7
55.5
56.1
69.6
69.4
57.2
68
53.3
47.9
60.8
61.7
57.8
51.4
50.5
48.1
58.7
54
56.1
60.4
51.2
50.7
56.4
53.3
52.6
47.7
49.5
48.5
55.3
49.8
57.4
64.6
53
41.5
55.9
58.4
53.5
50.6
58.5

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 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 & 0 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32502&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32502&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32502&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 time0 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Variance Reduction Matrix
V(Y[t],d=0,D=0)37.3612349726776Range28.5Trim Var.16.7536066763425
V(Y[t],d=1,D=0)55.6823276836158Range31.6Trim Var.39.3917260656883
V(Y[t],d=2,D=0)142.916130917592Range51.4Trim Var.98.1793323657475
V(Y[t],d=3,D=0)417.314107683001Range83.5Trim Var.289.958563348416
V(Y[t],d=0,D=1)42.5918962585034Range33.1Trim Var.19.7947328687573
V(Y[t],d=1,D=1)36.1969503546099Range25.3Trim Var.21.9045296167247
V(Y[t],d=2,D=1)99.5538482886217Range40.5Trim Var.57.330743902439
V(Y[t],d=3,D=1)320.986536231884Range77Trim Var.188.559685897436
V(Y[t],d=0,D=2)137.100855855856Range48.6Trim Var.82.9049621212121
V(Y[t],d=1,D=2)93.577492063492Range38.4Trim Var.65.0693447580645
V(Y[t],d=2,D=2)256.580554621849Range64.7Trim Var.172.001290322581
V(Y[t],d=3,D=2)797.504705882353Range112.4Trim Var.542.553436781609

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 37.3612349726776 & Range & 28.5 & Trim Var. & 16.7536066763425 \tabularnewline
V(Y[t],d=1,D=0) & 55.6823276836158 & Range & 31.6 & Trim Var. & 39.3917260656883 \tabularnewline
V(Y[t],d=2,D=0) & 142.916130917592 & Range & 51.4 & Trim Var. & 98.1793323657475 \tabularnewline
V(Y[t],d=3,D=0) & 417.314107683001 & Range & 83.5 & Trim Var. & 289.958563348416 \tabularnewline
V(Y[t],d=0,D=1) & 42.5918962585034 & Range & 33.1 & Trim Var. & 19.7947328687573 \tabularnewline
V(Y[t],d=1,D=1) & 36.1969503546099 & Range & 25.3 & Trim Var. & 21.9045296167247 \tabularnewline
V(Y[t],d=2,D=1) & 99.5538482886217 & Range & 40.5 & Trim Var. & 57.330743902439 \tabularnewline
V(Y[t],d=3,D=1) & 320.986536231884 & Range & 77 & Trim Var. & 188.559685897436 \tabularnewline
V(Y[t],d=0,D=2) & 137.100855855856 & Range & 48.6 & Trim Var. & 82.9049621212121 \tabularnewline
V(Y[t],d=1,D=2) & 93.577492063492 & Range & 38.4 & Trim Var. & 65.0693447580645 \tabularnewline
V(Y[t],d=2,D=2) & 256.580554621849 & Range & 64.7 & Trim Var. & 172.001290322581 \tabularnewline
V(Y[t],d=3,D=2) & 797.504705882353 & Range & 112.4 & Trim Var. & 542.553436781609 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32502&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]37.3612349726776[/C][C]Range[/C][C]28.5[/C][C]Trim Var.[/C][C]16.7536066763425[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]55.6823276836158[/C][C]Range[/C][C]31.6[/C][C]Trim Var.[/C][C]39.3917260656883[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]142.916130917592[/C][C]Range[/C][C]51.4[/C][C]Trim Var.[/C][C]98.1793323657475[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]417.314107683001[/C][C]Range[/C][C]83.5[/C][C]Trim Var.[/C][C]289.958563348416[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]42.5918962585034[/C][C]Range[/C][C]33.1[/C][C]Trim Var.[/C][C]19.7947328687573[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]36.1969503546099[/C][C]Range[/C][C]25.3[/C][C]Trim Var.[/C][C]21.9045296167247[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]99.5538482886217[/C][C]Range[/C][C]40.5[/C][C]Trim Var.[/C][C]57.330743902439[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]320.986536231884[/C][C]Range[/C][C]77[/C][C]Trim Var.[/C][C]188.559685897436[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]137.100855855856[/C][C]Range[/C][C]48.6[/C][C]Trim Var.[/C][C]82.9049621212121[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]93.577492063492[/C][C]Range[/C][C]38.4[/C][C]Trim Var.[/C][C]65.0693447580645[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]256.580554621849[/C][C]Range[/C][C]64.7[/C][C]Trim Var.[/C][C]172.001290322581[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]797.504705882353[/C][C]Range[/C][C]112.4[/C][C]Trim Var.[/C][C]542.553436781609[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32502&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32502&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)37.3612349726776Range28.5Trim Var.16.7536066763425
V(Y[t],d=1,D=0)55.6823276836158Range31.6Trim Var.39.3917260656883
V(Y[t],d=2,D=0)142.916130917592Range51.4Trim Var.98.1793323657475
V(Y[t],d=3,D=0)417.314107683001Range83.5Trim Var.289.958563348416
V(Y[t],d=0,D=1)42.5918962585034Range33.1Trim Var.19.7947328687573
V(Y[t],d=1,D=1)36.1969503546099Range25.3Trim Var.21.9045296167247
V(Y[t],d=2,D=1)99.5538482886217Range40.5Trim Var.57.330743902439
V(Y[t],d=3,D=1)320.986536231884Range77Trim Var.188.559685897436
V(Y[t],d=0,D=2)137.100855855856Range48.6Trim Var.82.9049621212121
V(Y[t],d=1,D=2)93.577492063492Range38.4Trim Var.65.0693447580645
V(Y[t],d=2,D=2)256.580554621849Range64.7Trim Var.172.001290322581
V(Y[t],d=3,D=2)797.504705882353Range112.4Trim Var.542.553436781609


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')