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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 computationTue, 09 Dec 2008 11:16:38 -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/2008/Dec/09/t1228846643sspnwluhowhwfwd.htm/, Retrieved Sun, 19 May 2024 08:48:38 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=31662, Retrieved Sun, 19 May 2024 08:48:38 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact168

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [(Partial) Autocorrelation Function] [step acf] [2008-12-09 15:39:34] [74be16979710d4c4e7c6647856088456]
F RMP     [Variance Reduction Matrix] [step 2 vrm] [2008-12-09 18:16:38] [d41d8cd98f00b204e9800998ecf8427e] [Current]
Feedback Forum
2008-12-15 15:37:38 [c00776cbed2786c9c4960950021bd861] [reply] 
De student(e) zegt dat de kleinste variantie hoort bij d=0 en D=1, dit is correct. Zo kunnen we afleiden hoeveel keer we seizoenaal en niet-seizoenaal moeten differentiëren.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
105.2
91.5
75.3
60.5
80.4
84.5
93.9
78
92.3
90
72.1
76.9
76
88.7
55.4
46.6
90.9
84.9
89
90.2
72.3
83
71.6
75.4
85.1
81.2
68.7
68.4
93.7
96.6
101.8
93.6
88.9
114.1
82.3
96.4
104
88.2
85.2
87.1
85.5
89.1
105.2
82.9
86.8
112
97.4
88.9
109.4
87.8
90.5
79.3
114.9
118.8
125
96.1
116.7
119.5
104.1
121
127.3
117.7
108
89.4
137.4
142
137.3
122.8
126.1
147.6
115.7
139.2
151.2
123.8
109
112.1
136.4
135.5
138.7
137.5
141.5
143.6
146.5
200.7
196.2

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'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31662&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31662&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31662&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'George Udny Yule' @ 72.249.76.132






Variance Reduction Matrix
V(Y[t],d=0,D=0)782.032535014005Range154.1Trim Var.425.910209009009
V(Y[t],d=1,D=0)298.093935742972Range87.5Trim Var.150.502600888560
V(Y[t],d=2,D=0)762.271222450779Range125.3Trim Var.457.064261796043
V(Y[t],d=3,D=0)2305.60620295092Range218.8Trim Var.1379.32934076682
V(Y[t],d=0,D=1)239.894383561644Range90.7Trim Var.133.702490384615
V(Y[t],d=1,D=1)247.100743348983Range69.4Trim Var.166.881624503968
V(Y[t],d=2,D=1)696.490410462777Range103.5Trim Var.503.66783922171
V(Y[t],d=3,D=1)2144.10803519669Range181.7Trim Var.1639.63216287678
V(Y[t],d=0,D=2)449.828131147541Range76.5Trim Var.326.175769230769
V(Y[t],d=1,D=2)611.769310734463Range107.5Trim Var.411.554119496855
V(Y[t],d=2,D=2)1781.07977790766Range164.5Trim Var.1300.01824383164
V(Y[t],d=3,D=2)5585.46030248034Range289.4Trim Var.4076.94589366516

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 782.032535014005 & Range & 154.1 & Trim Var. & 425.910209009009 \tabularnewline
V(Y[t],d=1,D=0) & 298.093935742972 & Range & 87.5 & Trim Var. & 150.502600888560 \tabularnewline
V(Y[t],d=2,D=0) & 762.271222450779 & Range & 125.3 & Trim Var. & 457.064261796043 \tabularnewline
V(Y[t],d=3,D=0) & 2305.60620295092 & Range & 218.8 & Trim Var. & 1379.32934076682 \tabularnewline
V(Y[t],d=0,D=1) & 239.894383561644 & Range & 90.7 & Trim Var. & 133.702490384615 \tabularnewline
V(Y[t],d=1,D=1) & 247.100743348983 & Range & 69.4 & Trim Var. & 166.881624503968 \tabularnewline
V(Y[t],d=2,D=1) & 696.490410462777 & Range & 103.5 & Trim Var. & 503.66783922171 \tabularnewline
V(Y[t],d=3,D=1) & 2144.10803519669 & Range & 181.7 & Trim Var. & 1639.63216287678 \tabularnewline
V(Y[t],d=0,D=2) & 449.828131147541 & Range & 76.5 & Trim Var. & 326.175769230769 \tabularnewline
V(Y[t],d=1,D=2) & 611.769310734463 & Range & 107.5 & Trim Var. & 411.554119496855 \tabularnewline
V(Y[t],d=2,D=2) & 1781.07977790766 & Range & 164.5 & Trim Var. & 1300.01824383164 \tabularnewline
V(Y[t],d=3,D=2) & 5585.46030248034 & Range & 289.4 & Trim Var. & 4076.94589366516 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31662&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]782.032535014005[/C][C]Range[/C][C]154.1[/C][C]Trim Var.[/C][C]425.910209009009[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]298.093935742972[/C][C]Range[/C][C]87.5[/C][C]Trim Var.[/C][C]150.502600888560[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]762.271222450779[/C][C]Range[/C][C]125.3[/C][C]Trim Var.[/C][C]457.064261796043[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]2305.60620295092[/C][C]Range[/C][C]218.8[/C][C]Trim Var.[/C][C]1379.32934076682[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]239.894383561644[/C][C]Range[/C][C]90.7[/C][C]Trim Var.[/C][C]133.702490384615[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]247.100743348983[/C][C]Range[/C][C]69.4[/C][C]Trim Var.[/C][C]166.881624503968[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]696.490410462777[/C][C]Range[/C][C]103.5[/C][C]Trim Var.[/C][C]503.66783922171[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]2144.10803519669[/C][C]Range[/C][C]181.7[/C][C]Trim Var.[/C][C]1639.63216287678[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]449.828131147541[/C][C]Range[/C][C]76.5[/C][C]Trim Var.[/C][C]326.175769230769[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]611.769310734463[/C][C]Range[/C][C]107.5[/C][C]Trim Var.[/C][C]411.554119496855[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]1781.07977790766[/C][C]Range[/C][C]164.5[/C][C]Trim Var.[/C][C]1300.01824383164[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]5585.46030248034[/C][C]Range[/C][C]289.4[/C][C]Trim Var.[/C][C]4076.94589366516[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31662&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31662&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)782.032535014005Range154.1Trim Var.425.910209009009
V(Y[t],d=1,D=0)298.093935742972Range87.5Trim Var.150.502600888560
V(Y[t],d=2,D=0)762.271222450779Range125.3Trim Var.457.064261796043
V(Y[t],d=3,D=0)2305.60620295092Range218.8Trim Var.1379.32934076682
V(Y[t],d=0,D=1)239.894383561644Range90.7Trim Var.133.702490384615
V(Y[t],d=1,D=1)247.100743348983Range69.4Trim Var.166.881624503968
V(Y[t],d=2,D=1)696.490410462777Range103.5Trim Var.503.66783922171
V(Y[t],d=3,D=1)2144.10803519669Range181.7Trim Var.1639.63216287678
V(Y[t],d=0,D=2)449.828131147541Range76.5Trim Var.326.175769230769
V(Y[t],d=1,D=2)611.769310734463Range107.5Trim Var.411.554119496855
V(Y[t],d=2,D=2)1781.07977790766Range164.5Trim Var.1300.01824383164
V(Y[t],d=3,D=2)5585.46030248034Range289.4Trim Var.4076.94589366516


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')