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Author*The author of this computation has been verified*
R Software Modulerwasp_grangercausality.wasp
Title produced by softwareBivariate Granger Causality
Date of computationSat, 05 Aug 2017 19:43:59 +0200
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2017/Aug/05/t15019550966ydg2x39czqrkuq.htm/, Retrieved Fri, 10 May 2024 18:22:02 +0200
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=, Retrieved Fri, 10 May 2024 18:22:02 +0200
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Original text written by user:
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User-defined keywords
Estimated Impact0
Dataseries X:
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
3
3
4
4
3
3
3
3
4
3
3
3
3
4
4
4
4
4
4
2
3
3
4
4
4
4
4
4
4
4
4
3
4
4
4
4
4
4
4
4
4
4
4
4
3
4
4
4
4
3
3
3
3
3
4
3
3
3
3
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
3
2
4
3
3
2
1
2
1
0
2
1
3
2
4
1
4
1
1
1
3
2
1
3
2
2
0
0
1
2
2
1
1
1
0
1
1
1
1
1
0
1
4
1
2
1
2
1
0
1
0
1
1
1
1
2
0
0
1
0
1
1
1
1
1
0
1
1
1
0
1
1
0
1
0
2
0
0
1
0
0
Dataseries Y:
2.47
2.94
2.76
2.65
2.76
2.76
2.24
2.24
1.88
2.12
2.35
2.41
1.59
1.53
1.35
0.94
1.53
1.47
1.29
1.24
1.35
1.35
1.18
1.00
1.06
1.29
1.41
1.00
1.35
1.29
1.47
1.35
1.53
1.47
1.65
1.35
1.53
0.76
1.59
1.06
1.65
1.35
1.53
1.41
1.47
1.71
1.76
1.59
1.47
1.24
1.24
1.53
1.41
1.41
1.35
1.59
1.65
1.29
1.47
1.24
1.29
1.82
1.12
1.65
1.41
1.12
1.59
0.47
1.47
1.41
1.53
1.18
1.35
1.12
1.06
0.82
0.59
0.76
1.06
0.76
0.76
0.76
0.76
1.06
0.94
0.65
0.73
0.59
0.59
0.65
0.82
0.59
0.71
0.47
0.53
0.59
0.71
0.59
0.59
0.59
0.59
0.47
0.82
0.47
0.65
0.53
1.41
0.76
0.65
0.59
0.65
0.65
0.82
0.76
1.76
0.29
0.65
0.59
0.53
0.53
0.53
0.53
0.53
0.53
0.59
0.53
0.65
0.59
0.59
0.53
0.65
0.53
0.82
0.47
0.41
0.53
0.47
0.41
0.53
0.59
0.76
0.59
0.65
0.82
0.82
0.47
0.59
0.59
0.59
0.82
0.88
0.71
1.82
0.59
0.53
0.71
0.65
0.71
0.65
0.76
2.76
1.71
1.24
1.82
1.24
0.76
1.18
0.82
0.82
0.59
1.12
0.71
1.12
0.82
0.76
0.41
0.88
0.71
1.24
0.94
1.06
1.00
0.71
0.47
0.76
0.71
0.71
0.18
0.88
0.71
0.76
0.71
0.53
0.41
0.41
0.29
0.35
0.71
0.41
0.53
0.00
0.41
2.71
0.71
0.71
0.47
0.47
0.47
0.41
0.35
0.41
0.41
0.24
0.35
0.59
0.47
0.47
0.06
0.41
0.29
0.47
0.41
0.41
0.71
0.41
0.00
0.65
0.47
1.12
0.71
0.47
0.82
0.59
0.35
0.00
1.12
0.65
0.59
0.41
0.35
0.71




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time2 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]2 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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 Outputview raw output of R engine
Computing time2 seconds
R ServerBig Analytics Cloud Computing Center







Granger Causality Test: Y = f(X)
ModelRes.DFDiff. DFFp-value
Complete model236
Reduced model237-10.1028247987792750.748749499028403

\begin{tabular}{lllllllll}
\hline
Granger Causality Test: Y = f(X) \tabularnewline
Model & Res.DF & Diff. DF & F & p-value \tabularnewline
Complete model & 236 &  &  &  \tabularnewline
Reduced model & 237 & -1 & 0.102824798779275 & 0.748749499028403 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&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]236[/C][C][/C][C][/C][C][/C][/ROW]
[ROW][C]Reduced model[/C][C]237[/C][C]-1[/C][C]0.102824798779275[/C][C]0.748749499028403[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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)
ModelRes.DFDiff. DFFp-value
Complete model236
Reduced model237-10.1028247987792750.748749499028403







Granger Causality Test: X = f(Y)
ModelRes.DFDiff. DFFp-value
Complete model236
Reduced model237-12.127978275443850.145961025588771

\begin{tabular}{lllllllll}
\hline
Granger Causality Test: X = f(Y) \tabularnewline
Model & Res.DF & Diff. DF & F & p-value \tabularnewline
Complete model & 236 &  &  &  \tabularnewline
Reduced model & 237 & -1 & 2.12797827544385 & 0.145961025588771 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&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]236[/C][C][/C][C][/C][C][/C][/ROW]
[ROW][C]Reduced model[/C][C]237[/C][C]-1[/C][C]2.12797827544385[/C][C]0.145961025588771[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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)
ModelRes.DFDiff. DFFp-value
Complete model236
Reduced model237-12.127978275443850.145961025588771



Parameters (Session):
par1 = 1 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 1 ; par6 = 1 ; par7 = 0 ; par8 = 1 ;
Parameters (R input):
par1 = 1 ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 1 ; par6 = 1 ; par7 = 0 ; par8 = 1 ;
R code (references can be found in the software module):
par8 <- '1'
par7 <- '0'
par6 <- '1'
par5 <- '1'
par4 <- '1'
par3 <- '0'
par2 <- '1'
par1 <- '1'
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)
print(x)
print(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')