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Author's title

Author

*Unverified author*

R Software Module

rwasp_grangercausality.wasp

Title produced by software

Bivariate Granger Causality

Date of computation

Wed, 06 Mar 2013 20:33:37 -0500

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Mar/06/t1362620258b9ab6oyg1k0ib07.htm/, Retrieved Sat, 04 May 2024 08:25:52 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=207536, Retrieved Sat, 04 May 2024 08:25:52 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Coffee

Estimated Impact

186

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-       [Bivariate Granger Causality] [Coffee Causality] [2013-03-07 01:33:37] [d41d8cd98f00b204e9800998ecf8427e] [Current]

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Dataseries X:

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Dataseries Y:

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Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	3 seconds
R Server	'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

\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 & 3 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=207536&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=207536&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=207536&T=0

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	3 seconds
R Server	'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

Granger Causality Test: Y = f(X)
Model	Res.DF	Diff. DF	F	p-value
Complete model	402
Reduced model	408	-6	3.08808949755756	0.00574244217809935

\begin{tabular}{lllllllll}
\hline
Granger Causality Test: Y = f(X) \tabularnewline
Model & Res.DF & Diff. DF & F & p-value \tabularnewline
Complete model & 402 &  &  &  \tabularnewline
Reduced model & 408 & -6 & 3.08808949755756 & 0.00574244217809935 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=207536&T=1

[TABLE]
[ROW][C]Granger Causality Test: Y = f(X)[/C][/ROW]
[ROW][C]Model[/C][C]Res.DF[/C][C]Diff. DF[/C][C]F[/C][C]p-value[/C][/ROW]
[ROW][C]Complete model[/C][C]402[/C][C][/C][C][/C][C][/C][/ROW]
[ROW][C]Reduced model[/C][C]408[/C][C]-6[/C][C]3.08808949755756[/C][C]0.00574244217809935[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=207536&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=207536&T=1

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Granger Causality Test: Y = f(X)
Model	Res.DF	Diff. DF	F	p-value
Complete model	402
Reduced model	408	-6	3.08808949755756	0.00574244217809935

Granger Causality Test: X = f(Y)
Model	Res.DF	Diff. DF	F	p-value
Complete model	402
Reduced model	408	-6	1.66768155891548	0.1275201492009

\begin{tabular}{lllllllll}
\hline
Granger Causality Test: X = f(Y) \tabularnewline
Model & Res.DF & Diff. DF & F & p-value \tabularnewline
Complete model & 402 &  &  &  \tabularnewline
Reduced model & 408 & -6 & 1.66768155891548 & 0.1275201492009 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=207536&T=2

[TABLE]
[ROW][C]Granger Causality Test: X = f(Y)[/C][/ROW]
[ROW][C]Model[/C][C]Res.DF[/C][C]Diff. DF[/C][C]F[/C][C]p-value[/C][/ROW]
[ROW][C]Complete model[/C][C]402[/C][C][/C][C][/C][C][/C][/ROW]
[ROW][C]Reduced model[/C][C]408[/C][C]-6[/C][C]1.66768155891548[/C][C]0.1275201492009[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=207536&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=207536&T=2

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Granger Causality Test: X = f(Y)
Model	Res.DF	Diff. DF	F	p-value
Complete model	402
Reduced model	408	-6	1.66768155891548	0.1275201492009

Figure 1

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Postscript link

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Figure 2

PNG link

Postscript link

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Figure 3

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Postscript link

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Parameters (Session):

par1 = 1 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 1 ; par6 = 1 ; par7 = 0 ; par8 = 6 ;

Parameters (R input):

par1 = 1 ; par2 = 1 ; par3 = 1 ; par4 = 1 ; par5 = 1 ; par6 = 1 ; par7 = 1 ; par8 = 6 ;

R code (references can be found in the software module):

library(lmtest)
par1 <- as.numeric(par1)
par2 <- as.numeric(par2)
par3 <- as.numeric(par3)
par4 <- as.numeric(par4)
par5 <- as.numeric(par5)
par6 <- as.numeric(par6)
par7 <- as.numeric(par7)
par8 <- as.numeric(par8)
ox <- x
oy <- y
if (par1 == 0) {
x <- log(x)
} else {
x <- (x ^ par1 - 1) / par1
}
if (par5 == 0) {
y <- log(y)
} else {
y <- (y ^ par5 - 1) / par5
}
if (par2 > 0) x <- diff(x,lag=1,difference=par2)
if (par6 > 0) y <- diff(y,lag=1,difference=par6)
if (par3 > 0) x <- diff(x,lag=par4,difference=par3)
if (par7 > 0) y <- diff(y,lag=par4,difference=par7)
x
y
(gyx <- grangertest(y ~ x, order=par8))
(gxy <- grangertest(x ~ y, order=par8))
bitmap(file='test1.png')
op <- par(mfrow=c(2,1))
(r <- ccf(ox,oy,main='Cross Correlation Function (raw data)',ylab='CCF',xlab='Lag (k)'))
(r <- ccf(x,y,main='Cross Correlation Function (transformed and differenced)',ylab='CCF',xlab='Lag (k)'))
par(op)
dev.off()
bitmap(file='test2.png')
op <- par(mfrow=c(2,1))
acf(ox,lag.max=round(length(x)/2),main='ACF of x (raw)')
acf(x,lag.max=round(length(x)/2),main='ACF of x (transformed and differenced)')
par(op)
dev.off()
bitmap(file='test3.png')
op <- par(mfrow=c(2,1))
acf(oy,lag.max=round(length(y)/2),main='ACF of y (raw)')
acf(y,lag.max=round(length(y)/2),main='ACF of y (transformed and differenced)')
par(op)
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Granger Causality Test: Y = f(X)',5,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Model',header=TRUE)
a<-table.element(a,'Res.DF',header=TRUE)
a<-table.element(a,'Diff. DF',header=TRUE)
a<-table.element(a,'F',header=TRUE)
a<-table.element(a,'p-value',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Complete model',header=TRUE)
a<-table.element(a,gyx$Res.Df[1])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Reduced model',header=TRUE)
a<-table.element(a,gyx$Res.Df[2])
a<-table.element(a,gyx$Df[2])
a<-table.element(a,gyx$F[2])
a<-table.element(a,gyx$Pr[2])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Granger Causality Test: X = f(Y)',5,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Model',header=TRUE)
a<-table.element(a,'Res.DF',header=TRUE)
a<-table.element(a,'Diff. DF',header=TRUE)
a<-table.element(a,'F',header=TRUE)
a<-table.element(a,'p-value',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Complete model',header=TRUE)
a<-table.element(a,gxy$Res.Df[1])
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.element(a,'')
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Reduced model',header=TRUE)
a<-table.element(a,gxy$Res.Df[2])
a<-table.element(a,gxy$Df[2])
a<-table.element(a,gxy$F[2])
a<-table.element(a,gxy$Pr[2])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable2.tab')

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Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code