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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, 07 Dec 2008 07:47:22 -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/07/t1228661278lmm88fueboo8kuf.htm/, Retrieved Sun, 19 May 2024 10:22:14 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=30027, Retrieved Sun, 19 May 2024 10:22:14 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact212

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] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMPD  [Standard Deviation-Mean Plot] [Identification an...] [2008-12-07 14:45:52] [b943bd7078334192ff8343563ee31113]
- RM        [Variance Reduction Matrix] [Identification an...] [2008-12-07 14:47:22] [620b6ad5c4696049e39cb73ce029682c] [Current]
- RMP         [(Partial) Autocorrelation Function] [Identification an...] [2008-12-07 14:51:36] [b943bd7078334192ff8343563ee31113]
F   P           [(Partial) Autocorrelation Function] [Identification an...] [2008-12-07 14:54:30] [b943bd7078334192ff8343563ee31113]
-   P             [(Partial) Autocorrelation Function] [Identification an...] [2008-12-07 14:58:01] [b943bd7078334192ff8343563ee31113]
F RMP               [Spectral Analysis] [Identification an...] [2008-12-07 15:02:51] [b943bd7078334192ff8343563ee31113]
F RMP                 [(Partial) Autocorrelation Function] [Identification an...] [2008-12-07 15:05:29] [b943bd7078334192ff8343563ee31113]
F RMP                   [ARIMA Backward Selection] [Identification an...] [2008-12-07 15:45:38] [b943bd7078334192ff8343563ee31113]
-   P                     [ARIMA Backward Selection] [ARIMA Backward Mo...] [2008-12-12 14:40:13] [b943bd7078334192ff8343563ee31113]
- RMP                       [ARIMA Forecasting] [ARIMA Forecasting...] [2008-12-15 17:00:29] [b943bd7078334192ff8343563ee31113]
F   P                         [ARIMA Forecasting] [ARIMA Forecasting...] [2008-12-15 18:00:13] [b943bd7078334192ff8343563ee31113]
-   P                     [ARIMA Backward Selection] [ARIMA Backward Mo...] [2008-12-12 14:46:56] [b943bd7078334192ff8343563ee31113]
-   P                       [ARIMA Backward Selection] [ARIMA ciska] [2008-12-20 21:03:45] [ed2ba3b6182103c15c0ab511ae4e6284]
-   P                       [ARIMA Backward Selection] [] [2008-12-20 22:26:43] [b98453cac15ba1066b407e146608df68]
- RMP                       [ARIMA Forecasting] [] [2008-12-20 22:29:20] [b98453cac15ba1066b407e146608df68]
- R PD                    [ARIMA Backward Selection] [ARIMA olie] [2008-12-20 13:29:28] [7458e879e85b911182071700fff19fbd]
-    D                      [ARIMA Backward Selection] [Arima BEL20] [2008-12-22 11:36:19] [7458e879e85b911182071700fff19fbd]
- RMP                       [ARIMA Backward Selection] [] [2009-12-28 20:46:18] [a171cf7519360d15de770637ace99f7a]
- RMPD                      [ARIMA Backward Selection] [] [2009-12-28 20:54:47] [a171cf7519360d15de770637ace99f7a]
-   P                   [(Partial) Autocorrelation Function] [Identification an...] [2008-12-12 12:38:52] [b943bd7078334192ff8343563ee31113]
-   P                 [Spectral Analysis] [Identification an...] [2008-12-12 12:35:01] [b943bd7078334192ff8343563ee31113]
-   PD                [Spectral Analysis] [Cumulatief perdio...] [2008-12-20 12:12:22] [74be16979710d4c4e7c6647856088456]
- RMPD          [Cross Correlation Function] [Kruiselingse corr...] [2008-12-12 19:52:52] [d32f94eec6fe2d8c421bd223368a5ced]
- RMPD          [Cross Correlation Function] [Kruiselingse corr...] [2008-12-12 19:54:41] [d32f94eec6fe2d8c421bd223368a5ced]
-    D            [Cross Correlation Function] [Test cross correl...] [2008-12-18 06:46:47] [d32f94eec6fe2d8c421bd223368a5ced]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1593
1477.9
1733.7
1569.7
1843.7
1950.3
1657.5
1772.1
1568.3
1809.8
1646.7
1808.5
1763.9
1625.5
1538.8
1342.4
1645.1
1619.9
1338.1
1505.5
1529.1
1511.9
1656.7
1694.4
1662.3
1588.7
1483.3
1585.6
1658.9
1584.4
1470.6
1618.7
1407.6
1473.9
1515.3
1485.4
1496.1
1493.5
1298.4
1375.3
1507.9
1455.3
1363.3
1392.8
1348.8
1880.3
1669.2
1543.6
1701.2
1516.5
1466.8
1484.1
1577.2
1684.5
1414.7
1674.5
1598.7
1739.1
1674.6
1671.8
1802
1526.8
1580.9
1634.8
1610.3
1712
1678.8
1708.1
1680.6
2056
1624
2021.4
1861.1
1750.8
1767.5
1710.3
2151.5
2047.9
1915.4
1984.7
1896.5
2170.8
2139.9
2330.5
2121.8
2226.8
1857.9
2155.9
2341.7
2290.2
2006.5
2111.9
1731.3
1762.2
1863.2
1943.5
1975.2

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=30027&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=30027&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30027&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)58160.7571069588Range1043.3Trim Var.38040.8784870356
V(Y[t],d=1,D=0)32492.1733289474Range963.5Trim Var.18667.8315458276
V(Y[t],d=2,D=0)97066.9429294513Range1636.8Trim Var.60515.4602745098
V(Y[t],d=3,D=0)330269.332039579Range3023.9Trim Var.209549.580360011
V(Y[t],d=0,D=1)44991.942022409Range949.8Trim Var.27708.1306954955
V(Y[t],d=1,D=1)37512.7821156053Range856.8Trim Var.21773.5082413921
V(Y[t],d=2,D=1)112705.330811049Range1485.4Trim Var.69097.2317884323
V(Y[t],d=3,D=1)378686.557700994Range2828.6Trim Var.224617.989475743
V(Y[t],d=0,D=2)88532.5991628615Range1359.1Trim Var.56079.9218846154
V(Y[t],d=1,D=2)97913.8780907668Range1624.9Trim Var.55960.4841964286
V(Y[t],d=2,D=2)289954.028559356Range2631Trim Var.168528.196287762
V(Y[t],d=3,D=2)964732.273507246Range4705Trim Var.559040.151573242

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 58160.7571069588 & Range & 1043.3 & Trim Var. & 38040.8784870356 \tabularnewline
V(Y[t],d=1,D=0) & 32492.1733289474 & Range & 963.5 & Trim Var. & 18667.8315458276 \tabularnewline
V(Y[t],d=2,D=0) & 97066.9429294513 & Range & 1636.8 & Trim Var. & 60515.4602745098 \tabularnewline
V(Y[t],d=3,D=0) & 330269.332039579 & Range & 3023.9 & Trim Var. & 209549.580360011 \tabularnewline
V(Y[t],d=0,D=1) & 44991.942022409 & Range & 949.8 & Trim Var. & 27708.1306954955 \tabularnewline
V(Y[t],d=1,D=1) & 37512.7821156053 & Range & 856.8 & Trim Var. & 21773.5082413921 \tabularnewline
V(Y[t],d=2,D=1) & 112705.330811049 & Range & 1485.4 & Trim Var. & 69097.2317884323 \tabularnewline
V(Y[t],d=3,D=1) & 378686.557700994 & Range & 2828.6 & Trim Var. & 224617.989475743 \tabularnewline
V(Y[t],d=0,D=2) & 88532.5991628615 & Range & 1359.1 & Trim Var. & 56079.9218846154 \tabularnewline
V(Y[t],d=1,D=2) & 97913.8780907668 & Range & 1624.9 & Trim Var. & 55960.4841964286 \tabularnewline
V(Y[t],d=2,D=2) & 289954.028559356 & Range & 2631 & Trim Var. & 168528.196287762 \tabularnewline
V(Y[t],d=3,D=2) & 964732.273507246 & Range & 4705 & Trim Var. & 559040.151573242 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30027&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]58160.7571069588[/C][C]Range[/C][C]1043.3[/C][C]Trim Var.[/C][C]38040.8784870356[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]32492.1733289474[/C][C]Range[/C][C]963.5[/C][C]Trim Var.[/C][C]18667.8315458276[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]97066.9429294513[/C][C]Range[/C][C]1636.8[/C][C]Trim Var.[/C][C]60515.4602745098[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]330269.332039579[/C][C]Range[/C][C]3023.9[/C][C]Trim Var.[/C][C]209549.580360011[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]44991.942022409[/C][C]Range[/C][C]949.8[/C][C]Trim Var.[/C][C]27708.1306954955[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]37512.7821156053[/C][C]Range[/C][C]856.8[/C][C]Trim Var.[/C][C]21773.5082413921[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]112705.330811049[/C][C]Range[/C][C]1485.4[/C][C]Trim Var.[/C][C]69097.2317884323[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]378686.557700994[/C][C]Range[/C][C]2828.6[/C][C]Trim Var.[/C][C]224617.989475743[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]88532.5991628615[/C][C]Range[/C][C]1359.1[/C][C]Trim Var.[/C][C]56079.9218846154[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]97913.8780907668[/C][C]Range[/C][C]1624.9[/C][C]Trim Var.[/C][C]55960.4841964286[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]289954.028559356[/C][C]Range[/C][C]2631[/C][C]Trim Var.[/C][C]168528.196287762[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]964732.273507246[/C][C]Range[/C][C]4705[/C][C]Trim Var.[/C][C]559040.151573242[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30027&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30027&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)58160.7571069588Range1043.3Trim Var.38040.8784870356
V(Y[t],d=1,D=0)32492.1733289474Range963.5Trim Var.18667.8315458276
V(Y[t],d=2,D=0)97066.9429294513Range1636.8Trim Var.60515.4602745098
V(Y[t],d=3,D=0)330269.332039579Range3023.9Trim Var.209549.580360011
V(Y[t],d=0,D=1)44991.942022409Range949.8Trim Var.27708.1306954955
V(Y[t],d=1,D=1)37512.7821156053Range856.8Trim Var.21773.5082413921
V(Y[t],d=2,D=1)112705.330811049Range1485.4Trim Var.69097.2317884323
V(Y[t],d=3,D=1)378686.557700994Range2828.6Trim Var.224617.989475743
V(Y[t],d=0,D=2)88532.5991628615Range1359.1Trim Var.56079.9218846154
V(Y[t],d=1,D=2)97913.8780907668Range1624.9Trim Var.55960.4841964286
V(Y[t],d=2,D=2)289954.028559356Range2631Trim Var.168528.196287762
V(Y[t],d=3,D=2)964732.273507246Range4705Trim Var.559040.151573242


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')