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 computationMon, 21 Dec 2009 05:58:42 -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/2009/Dec/21/t1261400466zhaxiqn60s99854.htm/, Retrieved Sun, 05 May 2024 10:16:59 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=70139, Retrieved Sun, 05 May 2024 10:16:59 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact118
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-12 13:32:37] [76963dc1903f0f612b6153510a3818cf]
- R  D  [Univariate Explorative Data Analysis] [Run Sequence gebo...] [2008-12-17 12:14:40] [76963dc1903f0f612b6153510a3818cf]
-         [Univariate Explorative Data Analysis] [Run Sequence Plot...] [2008-12-22 18:19:51] [1ce0d16c8f4225c977b42c8fa93bc163]
- RMP       [Variance Reduction Matrix] [Identifying Integ...] [2009-11-22 12:29:54] [b98453cac15ba1066b407e146608df68]
- R  D        [Variance Reduction Matrix] [] [2009-12-18 12:45:03] [ea26ab7ea3bba830cfeb08d06278d52c]
-    D            [Variance Reduction Matrix] [] [2009-12-21 12:58:42] [4f2ce09ae9ed345cd87786097de0b173] [Current]
Feedback Forum

Post a new message
Dataseries X:
3030.29
2803.47
2767.63
2882.6
2863.36
2897.06
3012.61
3142.95
3032.93
3045.78
3110.52
3013.24
2987.1
2995.55
2833.18
2848.96
2794.83
2845.26
2915.02
2892.63
2604.42
2641.65
2659.81
2638.53
2720.25
2745.88
2735.7
2811.7
2799.43
2555.28
2304.98
2214.95
2065.81
1940.49
2042
1995.37
1946.81
1765.9
1635.25
1833.42
1910.43
1959.67
1969.6
2061.41
2093.48
2120.88
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
2197.82
2014.45
1862.83
1905.41
1810.99
1670.07
1864.44
2052.02
2029.6
2070.83
2293.41
2443.27
2513.17
2466.92




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70139&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]1 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=70139&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70139&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Variance Reduction Matrix
V(Y[t],d=0,D=0)619236.520363452Range3061.71Trim Var.459780.13950395
V(Y[t],d=1,D=0)22076.1153973997Range998.81Trim Var.10604.2274043486
V(Y[t],d=2,D=0)31394.0483672414Range1260.98Trim Var.14296.9128180403
V(Y[t],d=3,D=0)84511.9166701874Range1886.22Trim Var.37409.5237402539
V(Y[t],d=0,D=1)700531.963636025Range3305.13Trim Var.470889.166325353
V(Y[t],d=1,D=1)44324.2553060557Range1737.68Trim Var.17137.3670137726
V(Y[t],d=2,D=1)64164.602971337Range1774.54Trim Var.23241.2047554231
V(Y[t],d=3,D=1)173678.787678678Range3134.28Trim Var.53747.3967892499
V(Y[t],d=0,D=2)922443.60137823Range5086.88Trim Var.473503.260229636
V(Y[t],d=1,D=2)123930.007214413Range2611.26Trim Var.53864.2895966724
V(Y[t],d=2,D=2)199592.533987237Range3158.78000000000Trim Var.72718.3225164267
V(Y[t],d=3,D=2)509199.288681163Range5192.03Trim Var.159589.387990063

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 619236.520363452 & Range & 3061.71 & Trim Var. & 459780.13950395 \tabularnewline
V(Y[t],d=1,D=0) & 22076.1153973997 & Range & 998.81 & Trim Var. & 10604.2274043486 \tabularnewline
V(Y[t],d=2,D=0) & 31394.0483672414 & Range & 1260.98 & Trim Var. & 14296.9128180403 \tabularnewline
V(Y[t],d=3,D=0) & 84511.9166701874 & Range & 1886.22 & Trim Var. & 37409.5237402539 \tabularnewline
V(Y[t],d=0,D=1) & 700531.963636025 & Range & 3305.13 & Trim Var. & 470889.166325353 \tabularnewline
V(Y[t],d=1,D=1) & 44324.2553060557 & Range & 1737.68 & Trim Var. & 17137.3670137726 \tabularnewline
V(Y[t],d=2,D=1) & 64164.602971337 & Range & 1774.54 & Trim Var. & 23241.2047554231 \tabularnewline
V(Y[t],d=3,D=1) & 173678.787678678 & Range & 3134.28 & Trim Var. & 53747.3967892499 \tabularnewline
V(Y[t],d=0,D=2) & 922443.60137823 & Range & 5086.88 & Trim Var. & 473503.260229636 \tabularnewline
V(Y[t],d=1,D=2) & 123930.007214413 & Range & 2611.26 & Trim Var. & 53864.2895966724 \tabularnewline
V(Y[t],d=2,D=2) & 199592.533987237 & Range & 3158.78000000000 & Trim Var. & 72718.3225164267 \tabularnewline
V(Y[t],d=3,D=2) & 509199.288681163 & Range & 5192.03 & Trim Var. & 159589.387990063 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70139&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]619236.520363452[/C][C]Range[/C][C]3061.71[/C][C]Trim Var.[/C][C]459780.13950395[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]22076.1153973997[/C][C]Range[/C][C]998.81[/C][C]Trim Var.[/C][C]10604.2274043486[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]31394.0483672414[/C][C]Range[/C][C]1260.98[/C][C]Trim Var.[/C][C]14296.9128180403[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]84511.9166701874[/C][C]Range[/C][C]1886.22[/C][C]Trim Var.[/C][C]37409.5237402539[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]700531.963636025[/C][C]Range[/C][C]3305.13[/C][C]Trim Var.[/C][C]470889.166325353[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]44324.2553060557[/C][C]Range[/C][C]1737.68[/C][C]Trim Var.[/C][C]17137.3670137726[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]64164.602971337[/C][C]Range[/C][C]1774.54[/C][C]Trim Var.[/C][C]23241.2047554231[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]173678.787678678[/C][C]Range[/C][C]3134.28[/C][C]Trim Var.[/C][C]53747.3967892499[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]922443.60137823[/C][C]Range[/C][C]5086.88[/C][C]Trim Var.[/C][C]473503.260229636[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]123930.007214413[/C][C]Range[/C][C]2611.26[/C][C]Trim Var.[/C][C]53864.2895966724[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]199592.533987237[/C][C]Range[/C][C]3158.78000000000[/C][C]Trim Var.[/C][C]72718.3225164267[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]509199.288681163[/C][C]Range[/C][C]5192.03[/C][C]Trim Var.[/C][C]159589.387990063[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70139&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70139&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)619236.520363452Range3061.71Trim Var.459780.13950395
V(Y[t],d=1,D=0)22076.1153973997Range998.81Trim Var.10604.2274043486
V(Y[t],d=2,D=0)31394.0483672414Range1260.98Trim Var.14296.9128180403
V(Y[t],d=3,D=0)84511.9166701874Range1886.22Trim Var.37409.5237402539
V(Y[t],d=0,D=1)700531.963636025Range3305.13Trim Var.470889.166325353
V(Y[t],d=1,D=1)44324.2553060557Range1737.68Trim Var.17137.3670137726
V(Y[t],d=2,D=1)64164.602971337Range1774.54Trim Var.23241.2047554231
V(Y[t],d=3,D=1)173678.787678678Range3134.28Trim Var.53747.3967892499
V(Y[t],d=0,D=2)922443.60137823Range5086.88Trim Var.473503.260229636
V(Y[t],d=1,D=2)123930.007214413Range2611.26Trim Var.53864.2895966724
V(Y[t],d=2,D=2)199592.533987237Range3158.78000000000Trim Var.72718.3225164267
V(Y[t],d=3,D=2)509199.288681163Range5192.03Trim Var.159589.387990063



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')