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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, 27 Nov 2009 06:45:38 -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/Nov/27/t1259329778mopeuhjisbwb7x9.htm/, Retrieved Sun, 28 Apr 2024 21:33:46 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=60765, Retrieved Sun, 28 Apr 2024 21:33:46 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsshwws8
Estimated Impact160

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [Q1 The Seatbeltlaw] [2007-11-14 19:27:43] [8cd6641b921d30ebe00b648d1481bba0]
- RMPD  [Multiple Regression] [Seatbelt] [2009-11-12 13:54:52] [b98453cac15ba1066b407e146608df68]
-    D    [Multiple Regression] [] [2009-11-20 13:47:03] [5482608004c1d7bbf873930172393a2d]
- RMPD        [Variance Reduction Matrix] [] [2009-11-27 13:45:38] [efdfe680cd785c4af09f858b30f777ec] [Current]
- RMP           [Spectral Analysis] [] [2009-11-27 13:52:24] [5482608004c1d7bbf873930172393a2d]
- RMP           [Spectral Analysis] [] [2009-11-27 13:55:38] [5482608004c1d7bbf873930172393a2d]
- RMP           [Spectral Analysis] [] [2009-11-27 13:57:49] [5482608004c1d7bbf873930172393a2d]
- RMP           [Standard Deviation-Mean Plot] [] [2009-11-27 14:01:45] [5482608004c1d7bbf873930172393a2d]
- RMPD            [ARIMA Backward Selection] [] [2009-12-02 15:22:59] [5482608004c1d7bbf873930172393a2d]
- RMPD            [Harrell-Davis Quantiles] [] [2009-12-02 15:38:18] [5482608004c1d7bbf873930172393a2d]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
6539
6699
6962
6981
7024
6940
6774
6671
6965
6969
6822
6878
6691
6837
7018
7167
7076
7171
7093
6971
7142
7047
6999
6650
6475
6437
6639
6422
6272
6232
6003
5673
6050
5977
5796
5752
5609
5839
6069
6006
5809
5797
5502
5568
5864
5764
5615
5615
5681
5915
6334
6494
6620
6578
6495
6538
6737
6651
6530
6563

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=60765&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=60765&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60765&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)261845.878813559Range1669Trim Var.218204.803633823
V(Y[t],d=1,D=0)30734.2109877265Range768Trim Var.20372.9862119013
V(Y[t],d=2,D=0)53844.8932244404Range1157Trim Var.34034.5682503771
V(Y[t],d=3,D=0)147053.131578947Range1965Trim Var.91706.4196078431
V(Y[t],d=0,D=1)30734.2109877265Range768Trim Var.20372.9862119013
V(Y[t],d=1,D=1)53844.8932244404Range1157Trim Var.34034.5682503771
V(Y[t],d=2,D=1)147053.131578947Range1965Trim Var.91706.4196078431
V(Y[t],d=3,D=1)458711.994805195Range3464Trim Var.300499.451428571
V(Y[t],d=0,D=2)53844.8932244404Range1157Trim Var.34034.5682503771
V(Y[t],d=1,D=2)147053.131578947Range1965Trim Var.91706.4196078431
V(Y[t],d=2,D=2)458711.994805195Range3464Trim Var.300499.451428571
V(Y[t],d=3,D=2)1531289.39528620Range6149Trim Var.1021799.97278912

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 261845.878813559 & Range & 1669 & Trim Var. & 218204.803633823 \tabularnewline
V(Y[t],d=1,D=0) & 30734.2109877265 & Range & 768 & Trim Var. & 20372.9862119013 \tabularnewline
V(Y[t],d=2,D=0) & 53844.8932244404 & Range & 1157 & Trim Var. & 34034.5682503771 \tabularnewline
V(Y[t],d=3,D=0) & 147053.131578947 & Range & 1965 & Trim Var. & 91706.4196078431 \tabularnewline
V(Y[t],d=0,D=1) & 30734.2109877265 & Range & 768 & Trim Var. & 20372.9862119013 \tabularnewline
V(Y[t],d=1,D=1) & 53844.8932244404 & Range & 1157 & Trim Var. & 34034.5682503771 \tabularnewline
V(Y[t],d=2,D=1) & 147053.131578947 & Range & 1965 & Trim Var. & 91706.4196078431 \tabularnewline
V(Y[t],d=3,D=1) & 458711.994805195 & Range & 3464 & Trim Var. & 300499.451428571 \tabularnewline
V(Y[t],d=0,D=2) & 53844.8932244404 & Range & 1157 & Trim Var. & 34034.5682503771 \tabularnewline
V(Y[t],d=1,D=2) & 147053.131578947 & Range & 1965 & Trim Var. & 91706.4196078431 \tabularnewline
V(Y[t],d=2,D=2) & 458711.994805195 & Range & 3464 & Trim Var. & 300499.451428571 \tabularnewline
V(Y[t],d=3,D=2) & 1531289.39528620 & Range & 6149 & Trim Var. & 1021799.97278912 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=60765&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]261845.878813559[/C][C]Range[/C][C]1669[/C][C]Trim Var.[/C][C]218204.803633823[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]30734.2109877265[/C][C]Range[/C][C]768[/C][C]Trim Var.[/C][C]20372.9862119013[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]53844.8932244404[/C][C]Range[/C][C]1157[/C][C]Trim Var.[/C][C]34034.5682503771[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]147053.131578947[/C][C]Range[/C][C]1965[/C][C]Trim Var.[/C][C]91706.4196078431[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]30734.2109877265[/C][C]Range[/C][C]768[/C][C]Trim Var.[/C][C]20372.9862119013[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]53844.8932244404[/C][C]Range[/C][C]1157[/C][C]Trim Var.[/C][C]34034.5682503771[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]147053.131578947[/C][C]Range[/C][C]1965[/C][C]Trim Var.[/C][C]91706.4196078431[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]458711.994805195[/C][C]Range[/C][C]3464[/C][C]Trim Var.[/C][C]300499.451428571[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]53844.8932244404[/C][C]Range[/C][C]1157[/C][C]Trim Var.[/C][C]34034.5682503771[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]147053.131578947[/C][C]Range[/C][C]1965[/C][C]Trim Var.[/C][C]91706.4196078431[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]458711.994805195[/C][C]Range[/C][C]3464[/C][C]Trim Var.[/C][C]300499.451428571[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]1531289.39528620[/C][C]Range[/C][C]6149[/C][C]Trim Var.[/C][C]1021799.97278912[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=60765&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=60765&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)261845.878813559Range1669Trim Var.218204.803633823
V(Y[t],d=1,D=0)30734.2109877265Range768Trim Var.20372.9862119013
V(Y[t],d=2,D=0)53844.8932244404Range1157Trim Var.34034.5682503771
V(Y[t],d=3,D=0)147053.131578947Range1965Trim Var.91706.4196078431
V(Y[t],d=0,D=1)30734.2109877265Range768Trim Var.20372.9862119013
V(Y[t],d=1,D=1)53844.8932244404Range1157Trim Var.34034.5682503771
V(Y[t],d=2,D=1)147053.131578947Range1965Trim Var.91706.4196078431
V(Y[t],d=3,D=1)458711.994805195Range3464Trim Var.300499.451428571
V(Y[t],d=0,D=2)53844.8932244404Range1157Trim Var.34034.5682503771
V(Y[t],d=1,D=2)147053.131578947Range1965Trim Var.91706.4196078431
V(Y[t],d=2,D=2)458711.994805195Range3464Trim Var.300499.451428571
V(Y[t],d=3,D=2)1531289.39528620Range6149Trim Var.1021799.97278912


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ;
Parameters (R input):
par1 = 1 ;
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')