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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_grangercausality.wasp
Title produced by softwareBivariate Granger Causality
Date of computationMon, 20 Dec 2010 21:57:55 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/20/t1292882189srx40kety06h7l2.htm/, Retrieved Fri, 03 May 2024 15:53:26 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=113148, Retrieved Fri, 03 May 2024 15:53:26 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact105
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Bivariate Granger Causality] [Paper Bivariate G...] [2010-12-20 21:57:55] [f38914513f1f4d866974b642cdd0baea] [Current]
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Dataseries X:
0.397232704
0.382767296
0.396037736
0.441761006
0.445220126
0.438490566
0.467484277
0.465786164
0.402075472
0.376163522
0.37591195
0.392955975
0.34490566
0.368553459
0.390880503
0.424842767
0.426855346
0.442327044
0.474842767
0.447610063
0.480754717
0.516037736
0.580628931
0.573522013
0.578867925
0.593584906
0.645974843
0.690503145
0.782201258
0.839056604
0.847484277
0.726855346
0.635534591
0.470943396
0.346163522
0.272327044
0.286792453
0.27672956
0.297421384
0.321698113
0.365597484
0.435220126
0.412893082
0.458679245
0.428427673
0.463522013
0.487169811
0.473584906
0.491886792
0.474842767
0.502327044
0.539371069
0.484402516
0.474654088
0.473522013
0.48754717
0.493333333
0.525157233
0.542704403
Dataseries Y:
0.504208603
0.457969746
0.509923035
0.606622221
0.626210885
0.626631316
0.676731276
0.613117455
0.486215861
0.452529881
0.467150592
0.494624486
0.444567428
0.478862605
0.544458459
0.628201498
0.672578445
0.652706633
0.645430599
0.576334011
0.618334234
0.639896351
0.72850438
0.694655375
0.689773225
0.712244845
0.760337031
0.837816503
0.90688735
0.976018259
0.962066806
0.837593417
0.767638807
0.580006349
0.387740568
0.331274078
0.345251272
0.380172806
0.399838692
0.425742404
0.524183377
0.597115327
0.541489699
0.615039426
0.547924872
0.574540743
0.603438956
0.577492342
0.614198564
0.584776957
0.62752366
0.676859979
0.645996894
0.596059959
0.585961029
0.607617528
0.598462423
0.638703699
0.64923164




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113148&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113148&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113148&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk







Granger Causality Test: Y = f(X)
ModelRes.DFDiff. DFFp-value
Complete model48
Reduced model51-31.719589021418330.175487302711464

\begin{tabular}{lllllllll}
\hline
Granger Causality Test: Y = f(X) \tabularnewline
Model & Res.DF & Diff. DF & F & p-value \tabularnewline
Complete model & 48 &  &  &  \tabularnewline
Reduced model & 51 & -3 & 1.71958902141833 & 0.175487302711464 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113148&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]48[/C][C][/C][C][/C][C][/C][/ROW]
[ROW][C]Reduced model[/C][C]51[/C][C]-3[/C][C]1.71958902141833[/C][C]0.175487302711464[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113148&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113148&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 model48
Reduced model51-31.719589021418330.175487302711464







Granger Causality Test: X = f(Y)
ModelRes.DFDiff. DFFp-value
Complete model48
Reduced model51-30.9923572599139520.404429532094952

\begin{tabular}{lllllllll}
\hline
Granger Causality Test: X = f(Y) \tabularnewline
Model & Res.DF & Diff. DF & F & p-value \tabularnewline
Complete model & 48 &  &  &  \tabularnewline
Reduced model & 51 & -3 & 0.992357259913952 & 0.404429532094952 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=113148&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]48[/C][C][/C][C][/C][C][/C][/ROW]
[ROW][C]Reduced model[/C][C]51[/C][C]-3[/C][C]0.992357259913952[/C][C]0.404429532094952[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=113148&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=113148&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 model48
Reduced model51-30.9923572599139520.404429532094952



Parameters (Session):
par1 = 1 ; par2 = 1 ; par3 = 0 ; par4 = 12 ; par5 = 1 ; par6 = 1 ; par7 = 0 ; par8 = 3 ;
Parameters (R input):
par1 = 1 ; par2 = 1 ; par3 = 0 ; par4 = 12 ; par5 = 1 ; par6 = 1 ; par7 = 0 ; par8 = 3 ;
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')