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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_rwalk.wasp
Title produced by softwareLaw of Averages
Date of computationSun, 30 Nov 2008 10:25:28 -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/Nov/30/t122806607413gs50ncq9hazvk.htm/, Retrieved Sun, 19 May 2024 07:20:29 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=26633, Retrieved Sun, 19 May 2024 07:20:29 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact227

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Law of Averages] [Random Walk Simul...] [2008-11-25 18:31:28] [b98453cac15ba1066b407e146608df68]
F         [Law of Averages] [q3 / 7] [2008-11-30 17:25:28] [6912578025c824de531bc660dd61b996] [Current]
F           [Law of Averages] [] [2008-12-01 17:21:21] [4ddbf81f78ea7c738951638c7e93f6ee]
F           [Law of Averages] [q3 taak 7] [2008-12-01 17:25:52] [7506b5e9e41ec66c6657f4234f97306e]
F           [Law of Averages] [q3 Taak 7] [2008-12-01 17:34:09] [491a70d26f8c977398d8a0c1c87d3dd4]
F           [Law of Averages] [Non Stationary Ti...] [2008-12-01 18:27:29] [79c17183721a40a589db5f9f561947d8]
-           [Law of Averages] [Q3] [2008-12-01 18:30:06] [b47fceb71c9525e79a89b5fc6d023d0e]
F           [Law of Averages] [] [2008-12-01 18:51:15] [c5e27150943bc3d623392efb0d98f8d3]
F           [Law of Averages] [Non Stationary Ti...] [2008-12-01 18:54:18] [db72903d7941c8279d5ce0e4e873d517]
F           [Law of Averages] [] [2008-12-01 22:50:13] [fad8a251ac01c156a8ae23a83577546f]
-           [Law of Averages] [verbetering Q3] [2008-12-07 09:58:38] [077ffec662d24c06be4c491541a44245]
Feedback Forum
2008-12-08 16:27:20 [Lindsay Heyndrickx] [reply] 
Hier wordt gebruik gemaakt van de nabla operator. Dit wordt gebruikt om tijdreeksen stationair te maken. De kleine d laat de spreiding aanpassen de grote D zorgt voor de seizonalteit. S wordt hier steeds door 12 vervangen omdat we met maanden werken. De variantie moet hier zo klein mogelijk zijn want dit is het deel dat we niet kunnen verklaren. De beste waarde staat dus op de tweede rij waar de variantie = 1.00190742931646. De kleine d is hier dus gelijk aan 1 en de grote D is hier gelijk aan nul.
2008-12-08 18:24:08 [Jan Cavents] [reply] 
zoals in je eigen taak en de comment van Lindsy, is het antwoord correct

Post a new message

Dataset

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=26633&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=26633&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=26633&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)85.225635270541Range37Trim Var.49.1448202959831
V(Y[t],d=1,D=0)1.00084506362122Range2Trim Var.NA
V(Y[t],d=2,D=0)1.93962166573740Range4Trim Var.0
V(Y[t],d=3,D=0)5.78224183812553Range8Trim Var.2.58787396518267
V(Y[t],d=0,D=1)12.9962635069176Range22Trim Var.6.05956886621688
V(Y[t],d=1,D=1)1.96706128898691Range4Trim Var.0
V(Y[t],d=2,D=1)3.70307581349964Range8Trim Var.0.968117757594739
V(Y[t],d=3,D=1)10.8263781204737Range16Trim Var.6.54097763048882
V(Y[t],d=0,D=2)27.1073507297656Range28Trim Var.12.1570857350574
V(Y[t],d=1,D=2)5.80583610926049Range8Trim Var.2.72419087761554
V(Y[t],d=2,D=2)10.7145698967895Range16Trim Var.6.50600092678406
V(Y[t],d=3,D=2)31.0761099365751Range28Trim Var.16.9562166677376

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 85.225635270541 & Range & 37 & Trim Var. & 49.1448202959831 \tabularnewline
V(Y[t],d=1,D=0) & 1.00084506362122 & Range & 2 & Trim Var. & NA \tabularnewline
V(Y[t],d=2,D=0) & 1.93962166573740 & Range & 4 & Trim Var. & 0 \tabularnewline
V(Y[t],d=3,D=0) & 5.78224183812553 & Range & 8 & Trim Var. & 2.58787396518267 \tabularnewline
V(Y[t],d=0,D=1) & 12.9962635069176 & Range & 22 & Trim Var. & 6.05956886621688 \tabularnewline
V(Y[t],d=1,D=1) & 1.96706128898691 & Range & 4 & Trim Var. & 0 \tabularnewline
V(Y[t],d=2,D=1) & 3.70307581349964 & Range & 8 & Trim Var. & 0.968117757594739 \tabularnewline
V(Y[t],d=3,D=1) & 10.8263781204737 & Range & 16 & Trim Var. & 6.54097763048882 \tabularnewline
V(Y[t],d=0,D=2) & 27.1073507297656 & Range & 28 & Trim Var. & 12.1570857350574 \tabularnewline
V(Y[t],d=1,D=2) & 5.80583610926049 & Range & 8 & Trim Var. & 2.72419087761554 \tabularnewline
V(Y[t],d=2,D=2) & 10.7145698967895 & Range & 16 & Trim Var. & 6.50600092678406 \tabularnewline
V(Y[t],d=3,D=2) & 31.0761099365751 & Range & 28 & Trim Var. & 16.9562166677376 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=26633&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]85.225635270541[/C][C]Range[/C][C]37[/C][C]Trim Var.[/C][C]49.1448202959831[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]1.00084506362122[/C][C]Range[/C][C]2[/C][C]Trim Var.[/C][C]NA[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=0)[/C][C]1.93962166573740[/C][C]Range[/C][C]4[/C][C]Trim Var.[/C][C]0[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=0)[/C][C]5.78224183812553[/C][C]Range[/C][C]8[/C][C]Trim Var.[/C][C]2.58787396518267[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]12.9962635069176[/C][C]Range[/C][C]22[/C][C]Trim Var.[/C][C]6.05956886621688[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]1.96706128898691[/C][C]Range[/C][C]4[/C][C]Trim Var.[/C][C]0[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=1)[/C][C]3.70307581349964[/C][C]Range[/C][C]8[/C][C]Trim Var.[/C][C]0.968117757594739[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]10.8263781204737[/C][C]Range[/C][C]16[/C][C]Trim Var.[/C][C]6.54097763048882[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]27.1073507297656[/C][C]Range[/C][C]28[/C][C]Trim Var.[/C][C]12.1570857350574[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]5.80583610926049[/C][C]Range[/C][C]8[/C][C]Trim Var.[/C][C]2.72419087761554[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]10.7145698967895[/C][C]Range[/C][C]16[/C][C]Trim Var.[/C][C]6.50600092678406[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]31.0761099365751[/C][C]Range[/C][C]28[/C][C]Trim Var.[/C][C]16.9562166677376[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=26633&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=26633&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)85.225635270541Range37Trim Var.49.1448202959831
V(Y[t],d=1,D=0)1.00084506362122Range2Trim Var.NA
V(Y[t],d=2,D=0)1.93962166573740Range4Trim Var.0
V(Y[t],d=3,D=0)5.78224183812553Range8Trim Var.2.58787396518267
V(Y[t],d=0,D=1)12.9962635069176Range22Trim Var.6.05956886621688
V(Y[t],d=1,D=1)1.96706128898691Range4Trim Var.0
V(Y[t],d=2,D=1)3.70307581349964Range8Trim Var.0.968117757594739
V(Y[t],d=3,D=1)10.8263781204737Range16Trim Var.6.54097763048882
V(Y[t],d=0,D=2)27.1073507297656Range28Trim Var.12.1570857350574
V(Y[t],d=1,D=2)5.80583610926049Range8Trim Var.2.72419087761554
V(Y[t],d=2,D=2)10.7145698967895Range16Trim Var.6.50600092678406
V(Y[t],d=3,D=2)31.0761099365751Range28Trim Var.16.9562166677376


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 500 ; par2 = 0.5 ;
Parameters (R input):
par1 = 500 ; par2 = 0.5 ;
R code (references can be found in the software module):
n <- as.numeric(par1)
p <- as.numeric(par2)
heads=rbinom(n-1,1,p)
a=2*(heads)-1
b=diffinv(a,xi=0)
c=1:n
pheads=(diffinv(heads,xi=.5))/c
bitmap(file='test1.png')
op=par(mfrow=c(2,1))
plot(c,b,type='n',main='Law of Averages',xlab='Toss Number',ylab='Excess of Heads',lwd=2,cex.lab=1.5,cex.main=2)
lines(c,b,col='red')
lines(c,rep(0,n),col='black')
plot(c,pheads,type='n',xlab='Toss Number',ylab='Proportion of Heads',lwd=2,cex.lab=1.5)
lines(c,pheads,col='blue')
lines(c,rep(.5,n),col='black')
par(op)
dev.off()
b
par1 <- as.numeric(12)
x <- as.array(b)
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')