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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_variancereduction.wasp
Title produced by softwareVariance Reduction Matrix
Date of computationSun, 07 Dec 2008 11:05:04 -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/t1228673125w88lpqxcnth1pm7.htm/, Retrieved Sun, 19 May 2024 12:01:43 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=30203, Retrieved Sun, 19 May 2024 12:01:43 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact159

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]
-   PD  [Univariate Data Series] [part 1] [2008-12-07 17:49:27] [74be16979710d4c4e7c6647856088456]
F RMPD      [Variance Reduction Matrix] [part 2] [2008-12-07 18:05:04] [d41d8cd98f00b204e9800998ecf8427e] [Current]
F RMP         [(Partial) Autocorrelation Function] [] [2008-12-07 18:08:51] [74be16979710d4c4e7c6647856088456]
F RMP           [Spectral Analysis] [part2] [2008-12-07 18:12:00] [74be16979710d4c4e7c6647856088456]
F   P             [Spectral Analysis] [part 2] [2008-12-07 18:24:43] [74be16979710d4c4e7c6647856088456]
F   P           [(Partial) Autocorrelation Function] [part 3] [2008-12-07 18:31:16] [74be16979710d4c4e7c6647856088456]
- RMP             [ARIMA Backward Selection] [eigen reeks stap 5] [2008-12-14 16:19:21] [b1bd16d1f47bfe13feacf1c27a0abba5]
Feedback Forum
2008-12-14 17:15:25 [Jasmine Hendrikx] [reply] 
Evaluatie stap 2 VRM:
De berekening is goed uitgevoerd en de juiste conclusie is genomen. We zien inderdaad bij de combinatie van d =1 en D=0 de kleinste variantie. Dit geldt ook voor de getrimde variantie.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
2174.56
2196.72
2350.44
2440.25
2408.64
2472.81
2407.6
2454.62
2448.05
2497.84
2645.64
2756.76
2849.27
2921.44
2981.85
3080.58
3106.22
3119.31
3061.26
3097.31
3161.69
3257.16
3277.01
3295.32
3363.99
3494.17
3667.03
3813.06
3917.96
3895.51
3801.06
3570.12
3701.61
3862.27
3970.1
4138.52
4199.75
4290.89
4443.91
4502.64
4356.98
4591.27
4696.96
4621.4
4562.84
4202.52
4296.49
4435.23
4105.18
4116.68
3844.49
3720.98
3674.4
3857.62
3801.06
3504.37
3032.6
3047.03
2962.34

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=30203&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=30203&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30203&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)515314.658843016Range2522.4Trim Var.408610.27866553
V(Y[t],d=1,D=0)20960.0194712644Range706.060000000001Trim Var.11572.6074058447
V(Y[t],d=2,D=0)31430.1512466792Range954.99Trim Var.15582.4998254118
V(Y[t],d=3,D=0)87792.9376794806Range1435.58000000000Trim Var.43999.1376580002
V(Y[t],d=0,D=1)471043.514094172Range2581.52Trim Var.299050.068000244
V(Y[t],d=1,D=1)31445.0195592270Range895.73Trim Var.14834.3239794231
V(Y[t],d=2,D=1)58692.8968043434Range1341.37Trim Var.23068.0939726046
V(Y[t],d=3,D=1)162551.246281342Range2321.41Trim Var.62844.9346753913
V(Y[t],d=0,D=2)627139.686294622Range2969.94Trim Var.431788.340203656
V(Y[t],d=1,D=2)83934.1632849376Range1481.9Trim Var.42625.0325274713
V(Y[t],d=2,D=2)155611.229567614Range2179.42Trim Var.62643.4029780789
V(Y[t],d=3,D=2)393451.323213609Range3144.96Trim Var.173325.389935979

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 515314.658843016 & Range & 2522.4 & Trim Var. & 408610.27866553 \tabularnewline
V(Y[t],d=1,D=0) & 20960.0194712644 & Range & 706.060000000001 & Trim Var. & 11572.6074058447 \tabularnewline
V(Y[t],d=2,D=0) & 31430.1512466792 & Range & 954.99 & Trim Var. & 15582.4998254118 \tabularnewline
V(Y[t],d=3,D=0) & 87792.9376794806 & Range & 1435.58000000000 & Trim Var. & 43999.1376580002 \tabularnewline
V(Y[t],d=0,D=1) & 471043.514094172 & Range & 2581.52 & Trim Var. & 299050.068000244 \tabularnewline
V(Y[t],d=1,D=1) & 31445.0195592270 & Range & 895.73 & Trim Var. & 14834.3239794231 \tabularnewline
V(Y[t],d=2,D=1) & 58692.8968043434 & Range & 1341.37 & Trim Var. & 23068.0939726046 \tabularnewline
V(Y[t],d=3,D=1) & 162551.246281342 & Range & 2321.41 & Trim Var. & 62844.9346753913 \tabularnewline
V(Y[t],d=0,D=2) & 627139.686294622 & Range & 2969.94 & Trim Var. & 431788.340203656 \tabularnewline
V(Y[t],d=1,D=2) & 83934.1632849376 & Range & 1481.9 & Trim Var. & 42625.0325274713 \tabularnewline
V(Y[t],d=2,D=2) & 155611.229567614 & Range & 2179.42 & Trim Var. & 62643.4029780789 \tabularnewline
V(Y[t],d=3,D=2) & 393451.323213609 & Range & 3144.96 & Trim Var. & 173325.389935979 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30203&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]515314.658843016[/C][C]Range[/C][C]2522.4[/C][C]Trim Var.[/C][C]408610.27866553[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]20960.0194712644[/C][C]Range[/C][C]706.060000000001[/C][C]Trim Var.[/C][C]11572.6074058447[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]31430.1512466792[/C][C]Range[/C][C]954.99[/C][C]Trim Var.[/C][C]15582.4998254118[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]87792.9376794806[/C][C]Range[/C][C]1435.58000000000[/C][C]Trim Var.[/C][C]43999.1376580002[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]471043.514094172[/C][C]Range[/C][C]2581.52[/C][C]Trim Var.[/C][C]299050.068000244[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]31445.0195592270[/C][C]Range[/C][C]895.73[/C][C]Trim Var.[/C][C]14834.3239794231[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]58692.8968043434[/C][C]Range[/C][C]1341.37[/C][C]Trim Var.[/C][C]23068.0939726046[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]162551.246281342[/C][C]Range[/C][C]2321.41[/C][C]Trim Var.[/C][C]62844.9346753913[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]627139.686294622[/C][C]Range[/C][C]2969.94[/C][C]Trim Var.[/C][C]431788.340203656[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]83934.1632849376[/C][C]Range[/C][C]1481.9[/C][C]Trim Var.[/C][C]42625.0325274713[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]155611.229567614[/C][C]Range[/C][C]2179.42[/C][C]Trim Var.[/C][C]62643.4029780789[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]393451.323213609[/C][C]Range[/C][C]3144.96[/C][C]Trim Var.[/C][C]173325.389935979[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30203&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30203&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)515314.658843016Range2522.4Trim Var.408610.27866553
V(Y[t],d=1,D=0)20960.0194712644Range706.060000000001Trim Var.11572.6074058447
V(Y[t],d=2,D=0)31430.1512466792Range954.99Trim Var.15582.4998254118
V(Y[t],d=3,D=0)87792.9376794806Range1435.58000000000Trim Var.43999.1376580002
V(Y[t],d=0,D=1)471043.514094172Range2581.52Trim Var.299050.068000244
V(Y[t],d=1,D=1)31445.0195592270Range895.73Trim Var.14834.3239794231
V(Y[t],d=2,D=1)58692.8968043434Range1341.37Trim Var.23068.0939726046
V(Y[t],d=3,D=1)162551.246281342Range2321.41Trim Var.62844.9346753913
V(Y[t],d=0,D=2)627139.686294622Range2969.94Trim Var.431788.340203656
V(Y[t],d=1,D=2)83934.1632849376Range1481.9Trim Var.42625.0325274713
V(Y[t],d=2,D=2)155611.229567614Range2179.42Trim Var.62643.4029780789
V(Y[t],d=3,D=2)393451.323213609Range3144.96Trim Var.173325.389935979


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')