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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 computationFri, 24 Dec 2010 11:50:15 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/24/t1293191333xk1xznvpvzvqx8a.htm/, Retrieved Tue, 30 Apr 2024 01:15:51 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=114781, Retrieved Tue, 30 Apr 2024 01:15:51 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact144

Tree of Dependent Computations

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  [Cross Correlation Function] [Q7 - zonder trans...] [2008-12-01 20:04:13] [299afd6311e4c20059ea2f05c8dd029d]
F RM D    [Variance Reduction Matrix] [Q8] [2008-12-01 20:20:44] [299afd6311e4c20059ea2f05c8dd029d]
F    D      [Variance Reduction Matrix] [Q8 - 2] [2008-12-01 20:25:07] [299afd6311e4c20059ea2f05c8dd029d]
F RM D        [Standard Deviation-Mean Plot] [Deel 2: Step 1] [2008-12-08 20:09:35] [299afd6311e4c20059ea2f05c8dd029d]
- RM D          [Variance Reduction Matrix] [Deel 2: Step 2 - VRM] [2008-12-08 20:13:17] [299afd6311e4c20059ea2f05c8dd029d]
-                 [Variance Reduction Matrix] [Totale Uitvoer - VRM] [2008-12-17 16:00:59] [299afd6311e4c20059ea2f05c8dd029d]
-  MPD                [Variance Reduction Matrix] [] [2010-12-24 11:50:15] [b91d9cfbf8712a09013bf3c2e3081c55] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1143,94
1227,85
1261,26
1408,95
1162,58
1259,39
1253,85
1475,32
1211,75
1303,83
1299,37
1430,73
1244,95
1318,58
1318,74
1525,05
1275,88
1360,09
1349,81
1574,04
1294,58
1380,60
1369,22
1565,98
1338,96
1457,57
1456,21
1654,44
1428,47
1530,39
1514,13
1698,25
1454,22
1578,06
1526,53
1714,21
1492,86
1593,42
1555,50
1820,55
1534,57
1636,03
1594,58
1805,13
1565,37
1679,57
1638,26
1854,64
1628,72
1744,97
1694,35
1920,88
1680,26
1778,62
1740,89
2010,56

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'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 & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=114781&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=114781&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=114781&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Variance Reduction Matrix
V(Y[t],d=0,D=0)41141.1930651623Range866.62Trim Var.28111.7903568980
V(Y[t],d=1,D=0)28120.4363853872Range555.65Trim Var.22722.9195301871
V(Y[t],d=2,D=0)95870.787218868Range938.47Trim Var.82182.060029743
V(Y[t],d=3,D=0)356149.745305298Range1792.47Trim Var.311977.795641258
V(Y[t],d=0,D=1)845.646447171945Range150.930000000000Trim Var.459.491220676329
V(Y[t],d=1,D=1)1201.66047317647Range167.9Trim Var.593.964105252524
V(Y[t],d=2,D=1)3443.19218465305Range309.900000000000Trim Var.1607.27646612050
V(Y[t],d=3,D=1)11465.6570627551Range523.23Trim Var.5700.27536101882
V(Y[t],d=0,D=2)2288.89279676418Range260.670000000000Trim Var.968.126093844367
V(Y[t],d=1,D=2)3644.78032099906Range328.950000000000Trim Var.1370.97895256097
V(Y[t],d=2,D=2)10664.5978442512Range565.119999999999Trim Var.4196.68273070511
V(Y[t],d=3,D=2)36096.0091361615Range944.209999999999Trim Var.14418.4819620782

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 41141.1930651623 & Range & 866.62 & Trim Var. & 28111.7903568980 \tabularnewline
V(Y[t],d=1,D=0) & 28120.4363853872 & Range & 555.65 & Trim Var. & 22722.9195301871 \tabularnewline
V(Y[t],d=2,D=0) & 95870.787218868 & Range & 938.47 & Trim Var. & 82182.060029743 \tabularnewline
V(Y[t],d=3,D=0) & 356149.745305298 & Range & 1792.47 & Trim Var. & 311977.795641258 \tabularnewline
V(Y[t],d=0,D=1) & 845.646447171945 & Range & 150.930000000000 & Trim Var. & 459.491220676329 \tabularnewline
V(Y[t],d=1,D=1) & 1201.66047317647 & Range & 167.9 & Trim Var. & 593.964105252524 \tabularnewline
V(Y[t],d=2,D=1) & 3443.19218465305 & Range & 309.900000000000 & Trim Var. & 1607.27646612050 \tabularnewline
V(Y[t],d=3,D=1) & 11465.6570627551 & Range & 523.23 & Trim Var. & 5700.27536101882 \tabularnewline
V(Y[t],d=0,D=2) & 2288.89279676418 & Range & 260.670000000000 & Trim Var. & 968.126093844367 \tabularnewline
V(Y[t],d=1,D=2) & 3644.78032099906 & Range & 328.950000000000 & Trim Var. & 1370.97895256097 \tabularnewline
V(Y[t],d=2,D=2) & 10664.5978442512 & Range & 565.119999999999 & Trim Var. & 4196.68273070511 \tabularnewline
V(Y[t],d=3,D=2) & 36096.0091361615 & Range & 944.209999999999 & Trim Var. & 14418.4819620782 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=114781&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]41141.1930651623[/C][C]Range[/C][C]866.62[/C][C]Trim Var.[/C][C]28111.7903568980[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]28120.4363853872[/C][C]Range[/C][C]555.65[/C][C]Trim Var.[/C][C]22722.9195301871[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]95870.787218868[/C][C]Range[/C][C]938.47[/C][C]Trim Var.[/C][C]82182.060029743[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]356149.745305298[/C][C]Range[/C][C]1792.47[/C][C]Trim Var.[/C][C]311977.795641258[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]845.646447171945[/C][C]Range[/C][C]150.930000000000[/C][C]Trim Var.[/C][C]459.491220676329[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]1201.66047317647[/C][C]Range[/C][C]167.9[/C][C]Trim Var.[/C][C]593.964105252524[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]3443.19218465305[/C][C]Range[/C][C]309.900000000000[/C][C]Trim Var.[/C][C]1607.27646612050[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]11465.6570627551[/C][C]Range[/C][C]523.23[/C][C]Trim Var.[/C][C]5700.27536101882[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]2288.89279676418[/C][C]Range[/C][C]260.670000000000[/C][C]Trim Var.[/C][C]968.126093844367[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]3644.78032099906[/C][C]Range[/C][C]328.950000000000[/C][C]Trim Var.[/C][C]1370.97895256097[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]10664.5978442512[/C][C]Range[/C][C]565.119999999999[/C][C]Trim Var.[/C][C]4196.68273070511[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]36096.0091361615[/C][C]Range[/C][C]944.209999999999[/C][C]Trim Var.[/C][C]14418.4819620782[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=114781&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=114781&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)41141.1930651623Range866.62Trim Var.28111.7903568980
V(Y[t],d=1,D=0)28120.4363853872Range555.65Trim Var.22722.9195301871
V(Y[t],d=2,D=0)95870.787218868Range938.47Trim Var.82182.060029743
V(Y[t],d=3,D=0)356149.745305298Range1792.47Trim Var.311977.795641258
V(Y[t],d=0,D=1)845.646447171945Range150.930000000000Trim Var.459.491220676329
V(Y[t],d=1,D=1)1201.66047317647Range167.9Trim Var.593.964105252524
V(Y[t],d=2,D=1)3443.19218465305Range309.900000000000Trim Var.1607.27646612050
V(Y[t],d=3,D=1)11465.6570627551Range523.23Trim Var.5700.27536101882
V(Y[t],d=0,D=2)2288.89279676418Range260.670000000000Trim Var.968.126093844367
V(Y[t],d=1,D=2)3644.78032099906Range328.950000000000Trim Var.1370.97895256097
V(Y[t],d=2,D=2)10664.5978442512Range565.119999999999Trim Var.4196.68273070511
V(Y[t],d=3,D=2)36096.0091361615Range944.209999999999Trim Var.14418.4819620782


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 4 ;
Parameters (R input):
par1 = 4 ;
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')