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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, 01 Dec 2008 13:34:07 -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/01/t12281637005ne0ujie494jdii.htm/, Retrieved Sun, 05 May 2024 09:49:33 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=27350, Retrieved Sun, 05 May 2024 09:49:33 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact240
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Data Series] [Airline data] [2007-10-18 09:58:47] [42daae401fd3def69a25014f2252b4c2]
F RMPD  [Variance Reduction Matrix] [Non Stationary Ti...] [2008-12-01 17:48:47] [b943bd7078334192ff8343563ee31113]
- RMP     [Spectral Analysis] [Non Stationary Ti...] [2008-12-01 19:56:04] [b943bd7078334192ff8343563ee31113]
- RMPD      [Cross Correlation Function] [Non Stationary Ti...] [2008-12-01 20:13:53] [b943bd7078334192ff8343563ee31113]
- RMPD        [(Partial) Autocorrelation Function] [Non Stationary Ti...] [2008-12-01 20:27:10] [b943bd7078334192ff8343563ee31113]
-   PD          [(Partial) Autocorrelation Function] [Non Stationary Ti...] [2008-12-01 20:29:06] [b943bd7078334192ff8343563ee31113]
-   P             [(Partial) Autocorrelation Function] [Non Stationary Ti...] [2008-12-01 20:31:48] [b943bd7078334192ff8343563ee31113]
- RMP                 [Variance Reduction Matrix] [Non Stationary Ti...] [2008-12-01 20:34:07] [620b6ad5c4696049e39cb73ce029682c] [Current]
- RMP                   [Spectral Analysis] [Non Stationary Ti...] [2008-12-01 20:37:58] [b943bd7078334192ff8343563ee31113]
- RMP                     [Standard Deviation-Mean Plot] [Non Stationary Ti...] [2008-12-01 20:41:45] [b943bd7078334192ff8343563ee31113]
- RMPD                      [(Partial) Autocorrelation Function] [Non Stationary Ti...] [2008-12-02 07:15:23] [b943bd7078334192ff8343563ee31113]
-   PD                        [(Partial) Autocorrelation Function] [Non Stationary Ti...] [2008-12-02 07:17:05] [b943bd7078334192ff8343563ee31113]
-   P                           [(Partial) Autocorrelation Function] [Non Stationary Ti...] [2008-12-02 07:19:06] [b943bd7078334192ff8343563ee31113]
- RMP                             [Variance Reduction Matrix] [Non Stationary Ti...] [2008-12-02 07:22:03] [b943bd7078334192ff8343563ee31113]
- RMP                               [Spectral Analysis] [Non Stationary Ti...] [2008-12-02 07:25:43] [b943bd7078334192ff8343563ee31113]
- RMP                                 [Standard Deviation-Mean Plot] [Non Stationary Ti...] [2008-12-02 07:32:20] [b943bd7078334192ff8343563ee31113]
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Dataseries X:
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




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 2 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=27350&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=27350&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27350&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 time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001







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=27350&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=27350&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27350&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)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



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')