FreeStatistics.org

Free Statistics

of Irreproducible Research!

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 computationWed, 26 Nov 2008 08:16:21 -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/26/t1227712645g22pvqpcbho6e6v.htm/, Retrieved Sun, 19 May 2024 06:42:47 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=25626, Retrieved Sun, 19 May 2024 06:42:47 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact223

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] [Herproducering VRM] [2008-11-26 15:16:21] [286e96bd53289970f8e5f25a93fb50b3] [Current]
F RMPD      [Variance Reduction Matrix] [Q6 VRM] [2008-11-27 15:11:08] [6fea0e9a9b3b29a63badf2c274e82506]
F RMPD      [Spectral Analysis] [Q6 Spectral d = 0...] [2008-11-27 15:28:24] [6fea0e9a9b3b29a63badf2c274e82506]
F RMPD      [Spectral Analysis] [Q6 Spectral d = 1...] [2008-11-27 15:34:25] [6fea0e9a9b3b29a63badf2c274e82506]
F RMPD      [Spectral Analysis] [Q6 Spectral d = 0...] [2008-11-27 15:39:52] [6fea0e9a9b3b29a63badf2c274e82506]
F RMPD      [Spectral Analysis] [Q6 Spectral d = 1...] [2008-11-27 15:57:09] [6fea0e9a9b3b29a63badf2c274e82506]
F RMPD      [Spectral Analysis] [Q6 Spectral d = 2...] [2008-11-27 16:03:24] [a18c43c8b63fa6800a53bb187b9ddd45]
F RMPD      [Spectral Analysis] [Q6 Spectral d = 1...] [2008-11-27 16:09:47] [6fea0e9a9b3b29a63badf2c274e82506]
-           [Law of Averages] [] [2008-12-08 18:46:21] [888addc516c3b812dd7be4bd54caa358]
-           [Law of Averages] [] [2008-12-09 08:06:40] [888addc516c3b812dd7be4bd54caa358]
Feedback Forum
2008-12-07 11:48:20 [Kevin Neelen] [reply] 
We zoeken naar een ideaal aantal graden van gewone differentiatie (d) en seizoensdifferentiatie (D). Deze wordt bereikt wanneer de variantie (kolom 2) het kleinst is. Deze module maakt de berekeningen en in deze Variance Reduction Matrix kunnen we zien dat de variantie het kleinst bij d=1 en D=0. Hier is de variatie dus stationair.
2008-12-09 00:36:10 [Michael Van Spaandonck] [reply] 
We zoeken naar een ideaal aantal graden van gewone differentiatie (d) en seizoensdifferentiatie (D). Deze wordt bereikt wanneer de variatie (kolom 2) het kleinst is. Deze module maakt de berekeningen en in deze tabel kunnen we zien dat de variatie het kleinst bij d=1 en D=0.
Hier is de reeks dus stationair en niet de variantie, zoals in het bijhorende document per vergissing gesteld wordt.

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=25626&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=25626&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=25626&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)45.765995991984Range31Trim Var.30.6016102282031
V(Y[t],d=1,D=0)1.00168207901747Range2Trim Var.NA
V(Y[t],d=2,D=0)2.04426559356137Range4Trim Var.0
V(Y[t],d=3,D=0)6.2015966768352Range8Trim Var.2.68490156448836
V(Y[t],d=0,D=1)10.2774430268960Range18Trim Var.4.26834104428288
V(Y[t],d=1,D=1)1.94231923002172Range4Trim Var.0
V(Y[t],d=2,D=1)3.99168469729753Range8Trim Var.2.19761800723785
V(Y[t],d=3,D=1)12.2065945301184Range16Trim Var.6.66585976930805
V(Y[t],d=0,D=2)19.7256965944272Range24Trim Var.10.2113833549602
V(Y[t],d=1,D=2)5.85625582944704Range8Trim Var.2.53208769541336
V(Y[t],d=2,D=2)12.3128964059197Range16Trim Var.6.49353534570724
V(Y[t],d=3,D=2)37.9237108969076Range28Trim Var.22.4175031327924

\begin{tabular}{lllllllll}
\hline
Variance Reduction Matrix \tabularnewline
V(Y[t],d=0,D=0) & 45.765995991984 & Range & 31 & Trim Var. & 30.6016102282031 \tabularnewline
V(Y[t],d=1,D=0) & 1.00168207901747 & Range & 2 & Trim Var. & NA \tabularnewline
V(Y[t],d=2,D=0) & 2.04426559356137 & Range & 4 & Trim Var. & 0 \tabularnewline
V(Y[t],d=3,D=0) & 6.2015966768352 & Range & 8 & Trim Var. & 2.68490156448836 \tabularnewline
V(Y[t],d=0,D=1) & 10.2774430268960 & Range & 18 & Trim Var. & 4.26834104428288 \tabularnewline
V(Y[t],d=1,D=1) & 1.94231923002172 & Range & 4 & Trim Var. & 0 \tabularnewline
V(Y[t],d=2,D=1) & 3.99168469729753 & Range & 8 & Trim Var. & 2.19761800723785 \tabularnewline
V(Y[t],d=3,D=1) & 12.2065945301184 & Range & 16 & Trim Var. & 6.66585976930805 \tabularnewline
V(Y[t],d=0,D=2) & 19.7256965944272 & Range & 24 & Trim Var. & 10.2113833549602 \tabularnewline
V(Y[t],d=1,D=2) & 5.85625582944704 & Range & 8 & Trim Var. & 2.53208769541336 \tabularnewline
V(Y[t],d=2,D=2) & 12.3128964059197 & Range & 16 & Trim Var. & 6.49353534570724 \tabularnewline
V(Y[t],d=3,D=2) & 37.9237108969076 & Range & 28 & Trim Var. & 22.4175031327924 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=25626&T=1

[TABLE]
[ROW][C]Variance Reduction Matrix[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=0)[/C][C]45.765995991984[/C][C]Range[/C][C]31[/C][C]Trim Var.[/C][C]30.6016102282031[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=0)[/C][C]1.00168207901747[/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]2.04426559356137[/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]6.2015966768352[/C][C]Range[/C][C]8[/C][C]Trim Var.[/C][C]2.68490156448836[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=1)[/C][C]10.2774430268960[/C][C]Range[/C][C]18[/C][C]Trim Var.[/C][C]4.26834104428288[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=1)[/C][C]1.94231923002172[/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]3.99168469729753[/C][C]Range[/C][C]8[/C][C]Trim Var.[/C][C]2.19761800723785[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=1)[/C][C]12.2065945301184[/C][C]Range[/C][C]16[/C][C]Trim Var.[/C][C]6.66585976930805[/C][/ROW]
[ROW][C]V(Y[t],d=0,D=2)[/C][C]19.7256965944272[/C][C]Range[/C][C]24[/C][C]Trim Var.[/C][C]10.2113833549602[/C][/ROW]
[ROW][C]V(Y[t],d=1,D=2)[/C][C]5.85625582944704[/C][C]Range[/C][C]8[/C][C]Trim Var.[/C][C]2.53208769541336[/C][/ROW]
[ROW][C]V(Y[t],d=2,D=2)[/C][C]12.3128964059197[/C][C]Range[/C][C]16[/C][C]Trim Var.[/C][C]6.49353534570724[/C][/ROW]
[ROW][C]V(Y[t],d=3,D=2)[/C][C]37.9237108969076[/C][C]Range[/C][C]28[/C][C]Trim Var.[/C][C]22.4175031327924[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=25626&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=25626&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)45.765995991984Range31Trim Var.30.6016102282031
V(Y[t],d=1,D=0)1.00168207901747Range2Trim Var.NA
V(Y[t],d=2,D=0)2.04426559356137Range4Trim Var.0
V(Y[t],d=3,D=0)6.2015966768352Range8Trim Var.2.68490156448836
V(Y[t],d=0,D=1)10.2774430268960Range18Trim Var.4.26834104428288
V(Y[t],d=1,D=1)1.94231923002172Range4Trim Var.0
V(Y[t],d=2,D=1)3.99168469729753Range8Trim Var.2.19761800723785
V(Y[t],d=3,D=1)12.2065945301184Range16Trim Var.6.66585976930805
V(Y[t],d=0,D=2)19.7256965944272Range24Trim Var.10.2113833549602
V(Y[t],d=1,D=2)5.85625582944704Range8Trim Var.2.53208769541336
V(Y[t],d=2,D=2)12.3128964059197Range16Trim Var.6.49353534570724
V(Y[t],d=3,D=2)37.9237108969076Range28Trim Var.22.4175031327924


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 500 ; par2 = 0.5 ;
Parameters (R input):
par1 = 500 ; par2 = 0.5 ; par3 = ; par4 = ; par5 = ; par6 = ; par7 = ; par8 = ; par9 = ; par10 = ; par11 = ; par12 = ; par13 = ; par14 = ; par15 = ; par16 = ; par17 = ; par18 = ; par19 = ; par20 = ;
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')