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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, 14 Dec 2008 08:44:19 -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/14/t1229269491iwjbnjjd4nrwoay.htm/, Retrieved Wed, 15 May 2024 08:39:42 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=33435, Retrieved Wed, 15 May 2024 08:39:42 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact187

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [Variance Reduction Matrix] [workshop] [2008-12-14 15:44:19] [821c4b3d195be8e737cf8c9dc649d3cf] [Current]
F RMP     [Spectral Analysis] [workshop] [2008-12-14 15:45:47] [3a9fc6d5b5e0e816787b7dbace57e7cd]
F   P       [Spectral Analysis] [workshop] [2008-12-14 15:47:26] [3a9fc6d5b5e0e816787b7dbace57e7cd]
F RMP         [Standard Deviation-Mean Plot] [workshop] [2008-12-14 15:48:50] [3a9fc6d5b5e0e816787b7dbace57e7cd]
F RMP           [(Partial) Autocorrelation Function] [workshop] [2008-12-14 15:50:28] [3a9fc6d5b5e0e816787b7dbace57e7cd]
F RMP             [ARIMA Backward Selection] [workshop] [2008-12-14 15:55:32] [3a9fc6d5b5e0e816787b7dbace57e7cd]
F RMP               [ARIMA Forecasting] [workshop] [2008-12-14 15:58:35] [3a9fc6d5b5e0e816787b7dbace57e7cd]
Feedback Forum
2008-12-23 23:06:14 [Anouk Greeve] [reply] 
Correcte berekeningen en juiste interpretatie. Ik kan er niet veel meer aan toevoegen.
2008-12-24 07:24:21 [Gert-Jan Geudens] [reply] 
Correcte conclusie. Voor meer informatie in verband met de VRM verwijzen we graag naar de vorige workshops waar dit reeds uitvoerig is besproken.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
2074
2049
2406
2558
2251
2059
2397
1747
1707
2319
1631
1627
1791
2034
1997
2169
2028
2253
2218
1855
2187
1852
1570
1851
1954
1828
2251
2277
2085
2282
2266
1878
2267
2069
1746
2299
2360
2214
2825
2355
2333
3016
2155
2172
2150
2533
2058
2160
2259
2498
2695
2799
2945
2930
2318
2540
2570
2669
2450
2842

Tables (Output of Computation)





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=33435&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=33435&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33435&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 time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001






Variance Reduction Matrix
V(Y[t],d=0,D=0)117743.998870057Range1446Trim Var.78607.1212438854
V(Y[t],d=1,D=0)109972.154880187Range1544Trim Var.67608.1342525399
V(Y[t],d=2,D=0)312785.840592861Range2422Trim Var.201888.514328808
V(Y[t],d=3,D=0)987654.446115288Range4671Trim Var.614114.188235294
V(Y[t],d=0,D=1)82846.7925531915Range1201Trim Var.50602.2049941928
V(Y[t],d=1,D=1)131507.471785384Range1528Trim Var.74690.6890243902
V(Y[t],d=2,D=1)394497.143961353Range2684Trim Var.233688.455769231
V(Y[t],d=3,D=1)1278642.93636364Range4738Trim Var.768528.357624831
V(Y[t],d=0,D=2)165611.777777778Range1641Trim Var.109564.157258065
V(Y[t],d=1,D=2)342289.915966387Range2278Trim Var.237264.995698925
V(Y[t],d=2,D=2)1020005.16577540Range3809Trim Var.740845.564367816
V(Y[t],d=3,D=2)3333131.46022727Range7032Trim Var.2363797.25123153

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 117743.998870057 & Range & 1446 & Trim Var. & 78607.1212438854 \tabularnewline
V(Y[t],d=1,D=0) & 109972.154880187 & Range & 1544 & Trim Var. & 67608.1342525399 \tabularnewline
V(Y[t],d=2,D=0) & 312785.840592861 & Range & 2422 & Trim Var. & 201888.514328808 \tabularnewline
V(Y[t],d=3,D=0) & 987654.446115288 & Range & 4671 & Trim Var. & 614114.188235294 \tabularnewline
V(Y[t],d=0,D=1) & 82846.7925531915 & Range & 1201 & Trim Var. & 50602.2049941928 \tabularnewline
V(Y[t],d=1,D=1) & 131507.471785384 & Range & 1528 & Trim Var. & 74690.6890243902 \tabularnewline
V(Y[t],d=2,D=1) & 394497.143961353 & Range & 2684 & Trim Var. & 233688.455769231 \tabularnewline
V(Y[t],d=3,D=1) & 1278642.93636364 & Range & 4738 & Trim Var. & 768528.357624831 \tabularnewline
V(Y[t],d=0,D=2) & 165611.777777778 & Range & 1641 & Trim Var. & 109564.157258065 \tabularnewline
V(Y[t],d=1,D=2) & 342289.915966387 & Range & 2278 & Trim Var. & 237264.995698925 \tabularnewline
V(Y[t],d=2,D=2) & 1020005.16577540 & Range & 3809 & Trim Var. & 740845.564367816 \tabularnewline
V(Y[t],d=3,D=2) & 3333131.46022727 & Range & 7032 & Trim Var. & 2363797.25123153 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33435&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]117743.998870057[/C][C]Range[/C][C]1446[/C][C]Trim Var.[/C][C]78607.1212438854[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]109972.154880187[/C][C]Range[/C][C]1544[/C][C]Trim Var.[/C][C]67608.1342525399[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]312785.840592861[/C][C]Range[/C][C]2422[/C][C]Trim Var.[/C][C]201888.514328808[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]987654.446115288[/C][C]Range[/C][C]4671[/C][C]Trim Var.[/C][C]614114.188235294[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]82846.7925531915[/C][C]Range[/C][C]1201[/C][C]Trim Var.[/C][C]50602.2049941928[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]131507.471785384[/C][C]Range[/C][C]1528[/C][C]Trim Var.[/C][C]74690.6890243902[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]394497.143961353[/C][C]Range[/C][C]2684[/C][C]Trim Var.[/C][C]233688.455769231[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]1278642.93636364[/C][C]Range[/C][C]4738[/C][C]Trim Var.[/C][C]768528.357624831[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]165611.777777778[/C][C]Range[/C][C]1641[/C][C]Trim Var.[/C][C]109564.157258065[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]342289.915966387[/C][C]Range[/C][C]2278[/C][C]Trim Var.[/C][C]237264.995698925[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]1020005.16577540[/C][C]Range[/C][C]3809[/C][C]Trim Var.[/C][C]740845.564367816[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]3333131.46022727[/C][C]Range[/C][C]7032[/C][C]Trim Var.[/C][C]2363797.25123153[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33435&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33435&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)117743.998870057Range1446Trim Var.78607.1212438854
V(Y[t],d=1,D=0)109972.154880187Range1544Trim Var.67608.1342525399
V(Y[t],d=2,D=0)312785.840592861Range2422Trim Var.201888.514328808
V(Y[t],d=3,D=0)987654.446115288Range4671Trim Var.614114.188235294
V(Y[t],d=0,D=1)82846.7925531915Range1201Trim Var.50602.2049941928
V(Y[t],d=1,D=1)131507.471785384Range1528Trim Var.74690.6890243902
V(Y[t],d=2,D=1)394497.143961353Range2684Trim Var.233688.455769231
V(Y[t],d=3,D=1)1278642.93636364Range4738Trim Var.768528.357624831
V(Y[t],d=0,D=2)165611.777777778Range1641Trim Var.109564.157258065
V(Y[t],d=1,D=2)342289.915966387Range2278Trim Var.237264.995698925
V(Y[t],d=2,D=2)1020005.16577540Range3809Trim Var.740845.564367816
V(Y[t],d=3,D=2)3333131.46022727Range7032Trim Var.2363797.25123153


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')