Free Statistics

of Irreproducible Research!

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 03:58:24 -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/t1229079647yxgqjnznwmbenz3.htm/, Retrieved Fri, 17 May 2024 18:11:00 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=32539, Retrieved Fri, 17 May 2024 18:11:00 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact239
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]
- R PD  [Univariate Data Series] [Tijdreeks 2 Buite...] [2008-12-11 16:25:30] [2d4aec5ed1856c4828162be37be304d9]
- RMP     [Central Tendency] [Central tendency ...] [2008-12-11 17:41:16] [2d4aec5ed1856c4828162be37be304d9]
- RMP       [Blocked Bootstrap Plot - Central Tendency] [Blocked Bootstrap...] [2008-12-12 08:14:08] [2d4aec5ed1856c4828162be37be304d9]
- RMP         [Tukey lambda PPCC Plot] [Tukey Lambda PPCC...] [2008-12-12 08:45:26] [2d4aec5ed1856c4828162be37be304d9]
- RMP           [Univariate Explorative Data Analysis] [Lag plot + ACF Ti...] [2008-12-12 08:54:04] [2d4aec5ed1856c4828162be37be304d9]
- RMP               [Variance Reduction Matrix] [VRM tijdreeks 2] [2008-12-12 10:58:24] [d7f41258beeebb8716e3f5d39f3cdc01] [Current]
- RMP                 [Spectral Analysis] [Spectrum tijdreeks 2] [2008-12-12 11:59:54] [2d4aec5ed1856c4828162be37be304d9]
- RMP                 [(Partial) Autocorrelation Function] [P(ACF) Tijdreeks ...] [2008-12-12 12:11:12] [2d4aec5ed1856c4828162be37be304d9]
- RMP                 [(Partial) Autocorrelation Function] [P(ACF) Tijdreeks ...] [2008-12-12 12:17:09] [2d4aec5ed1856c4828162be37be304d9]
- RMP                   [ARIMA Backward Selection] [ARIMA Backward Se...] [2008-12-12 12:29:19] [2d4aec5ed1856c4828162be37be304d9]
- RMPD                    [Bivariate Kernel Density Estimation] [Bivariate Kernel ...] [2008-12-22 09:26:11] [2d4aec5ed1856c4828162be37be304d9]
- RMPD                      [Kendall tau Correlation Matrix] [Kendall Tau Corre...] [2008-12-22 09:35:25] [2d4aec5ed1856c4828162be37be304d9]
- RM D                        [Pearson Correlation] [Pearson correlati...] [2008-12-22 09:46:51] [2d4aec5ed1856c4828162be37be304d9]
- RMP                           [Cross Correlation Function] [Cross Correlation...] [2008-12-22 10:31:31] [2d4aec5ed1856c4828162be37be304d9]
-   P                             [Cross Correlation Function] [Cross Correlation...] [2008-12-22 11:21:14] [2d4aec5ed1856c4828162be37be304d9]
- RMP                     [ARIMA Forecasting] [Arima forecast (p...] [2008-12-22 15:10:16] [2d4aec5ed1856c4828162be37be304d9]
-    D                [Variance Reduction Matrix] [VRM Xt] [2008-12-22 11:17:14] [2d4aec5ed1856c4828162be37be304d9]
Feedback Forum

Post a new message
Dataseries X:
2220.6
2161.5
1863.6
1955.1
1907.4
1889.4
2246.3
2213
1965
2285.6
1983.8
1872.4
2371.4
2287
2198.2
2330.4
2014.4
2066.1
2355.8
2232.5
2091.7
2376.5
1931.9
2025.7
2404.9
2316.1
2368.1
2282.5
2158.6
2174.8
2594.1
2281.4
2547.9
2606.3
2190.8
2262.3
2423.8
2520.4
2482.9
2215.9
2441.9
2333.8
2670.2
2431
2559.3
2661.4
2404.6
2378.3
2489.2
2941
2700.9
2335.6
2770
2764.2
2784.9
2898.8
2853.4
3022.6
2851.4
2630.8




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 3 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32539&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32539&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32539&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 time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Variance Reduction Matrix
V(Y[t],d=0,D=0)83909.425661017Range1159Trim Var.59926.8430468204
V(Y[t],d=1,D=0)54195.9794330801Range943.6Trim Var.38451.0503483309
V(Y[t],d=2,D=0)148912.355369026Range1531.7Trim Var.109692.136662896
V(Y[t],d=3,D=0)463897.030363409Range2551.1Trim Var.346930.125435294
V(Y[t],d=0,D=1)19402.3097828014Range534.4Trim Var.12528.8977526132
V(Y[t],d=1,D=1)31902.5901850139Range723Trim Var.20677.0218780488
V(Y[t],d=2,D=1)101154.265082126Range1302.5Trim Var.63465.9647115384
V(Y[t],d=3,D=1)339733.961191919Range2317.2Trim Var.215512.219919028
V(Y[t],d=0,D=2)35737.5601587302Range774.3Trim Var.20208.4088608871
V(Y[t],d=1,D=2)43709.7596302521Range1005.9Trim Var.27290.0122365591
V(Y[t],d=2,D=2)143782.041960784Range1624Trim Var.89213.9306781608
V(Y[t],d=3,D=2)524205.248712121Range2908.5Trim Var.353385.523128079

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 83909.425661017 & Range & 1159 & Trim Var. & 59926.8430468204 \tabularnewline
V(Y[t],d=1,D=0) & 54195.9794330801 & Range & 943.6 & Trim Var. & 38451.0503483309 \tabularnewline
V(Y[t],d=2,D=0) & 148912.355369026 & Range & 1531.7 & Trim Var. & 109692.136662896 \tabularnewline
V(Y[t],d=3,D=0) & 463897.030363409 & Range & 2551.1 & Trim Var. & 346930.125435294 \tabularnewline
V(Y[t],d=0,D=1) & 19402.3097828014 & Range & 534.4 & Trim Var. & 12528.8977526132 \tabularnewline
V(Y[t],d=1,D=1) & 31902.5901850139 & Range & 723 & Trim Var. & 20677.0218780488 \tabularnewline
V(Y[t],d=2,D=1) & 101154.265082126 & Range & 1302.5 & Trim Var. & 63465.9647115384 \tabularnewline
V(Y[t],d=3,D=1) & 339733.961191919 & Range & 2317.2 & Trim Var. & 215512.219919028 \tabularnewline
V(Y[t],d=0,D=2) & 35737.5601587302 & Range & 774.3 & Trim Var. & 20208.4088608871 \tabularnewline
V(Y[t],d=1,D=2) & 43709.7596302521 & Range & 1005.9 & Trim Var. & 27290.0122365591 \tabularnewline
V(Y[t],d=2,D=2) & 143782.041960784 & Range & 1624 & Trim Var. & 89213.9306781608 \tabularnewline
V(Y[t],d=3,D=2) & 524205.248712121 & Range & 2908.5 & Trim Var. & 353385.523128079 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32539&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]83909.425661017[/C][C]Range[/C][C]1159[/C][C]Trim Var.[/C][C]59926.8430468204[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]54195.9794330801[/C][C]Range[/C][C]943.6[/C][C]Trim Var.[/C][C]38451.0503483309[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]148912.355369026[/C][C]Range[/C][C]1531.7[/C][C]Trim Var.[/C][C]109692.136662896[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]463897.030363409[/C][C]Range[/C][C]2551.1[/C][C]Trim Var.[/C][C]346930.125435294[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]19402.3097828014[/C][C]Range[/C][C]534.4[/C][C]Trim Var.[/C][C]12528.8977526132[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]31902.5901850139[/C][C]Range[/C][C]723[/C][C]Trim Var.[/C][C]20677.0218780488[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]101154.265082126[/C][C]Range[/C][C]1302.5[/C][C]Trim Var.[/C][C]63465.9647115384[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]339733.961191919[/C][C]Range[/C][C]2317.2[/C][C]Trim Var.[/C][C]215512.219919028[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]35737.5601587302[/C][C]Range[/C][C]774.3[/C][C]Trim Var.[/C][C]20208.4088608871[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]43709.7596302521[/C][C]Range[/C][C]1005.9[/C][C]Trim Var.[/C][C]27290.0122365591[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]143782.041960784[/C][C]Range[/C][C]1624[/C][C]Trim Var.[/C][C]89213.9306781608[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]524205.248712121[/C][C]Range[/C][C]2908.5[/C][C]Trim Var.[/C][C]353385.523128079[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32539&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32539&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)83909.425661017Range1159Trim Var.59926.8430468204
V(Y[t],d=1,D=0)54195.9794330801Range943.6Trim Var.38451.0503483309
V(Y[t],d=2,D=0)148912.355369026Range1531.7Trim Var.109692.136662896
V(Y[t],d=3,D=0)463897.030363409Range2551.1Trim Var.346930.125435294
V(Y[t],d=0,D=1)19402.3097828014Range534.4Trim Var.12528.8977526132
V(Y[t],d=1,D=1)31902.5901850139Range723Trim Var.20677.0218780488
V(Y[t],d=2,D=1)101154.265082126Range1302.5Trim Var.63465.9647115384
V(Y[t],d=3,D=1)339733.961191919Range2317.2Trim Var.215512.219919028
V(Y[t],d=0,D=2)35737.5601587302Range774.3Trim Var.20208.4088608871
V(Y[t],d=1,D=2)43709.7596302521Range1005.9Trim Var.27290.0122365591
V(Y[t],d=2,D=2)143782.041960784Range1624Trim Var.89213.9306781608
V(Y[t],d=3,D=2)524205.248712121Range2908.5Trim Var.353385.523128079



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')