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Description of Statistical Computation

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 computationWed, 23 Dec 2009 10:42:26 -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/2009/Dec/23/t12615909230u72st04b2pb9tz.htm/, Retrieved Mon, 29 Apr 2024 08:45:45 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=70557, Retrieved Mon, 29 Apr 2024 08:45:45 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact143

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Standard Deviation-Mean Plot] [deel1 st dev mean...] [2009-12-16 19:13:20] [95cead3ebb75668735f848316249436a]
- RMP   [(Partial) Autocorrelation Function] [deel1 acf D=d=0] [2009-12-16 19:17:58] [95cead3ebb75668735f848316249436a]
-         [(Partial) Autocorrelation Function] [deel1 acf D=d=1] [2009-12-16 19:21:27] [95cead3ebb75668735f848316249436a]
- RM        [Variance Reduction Matrix] [deel1 vrm] [2009-12-16 19:23:09] [95cead3ebb75668735f848316249436a]
- RM          [Spectral Analysis] [deel1 spectrum D=d=1] [2009-12-16 19:31:03] [95cead3ebb75668735f848316249436a]
- RMP           [ARIMA Forecasting] [deel1 arima forca...] [2009-12-18 14:46:40] [95cead3ebb75668735f848316249436a]
- RMPD            [Bivariate Granger Causality] [Granger Causality] [2009-12-19 17:16:50] [95cead3ebb75668735f848316249436a]
-   P                 [Bivariate Granger Causality] [granger causality...] [2009-12-23 17:42:26] [95523ebdb89b97dbf680ec91e0b4bca2] [Current]
-                       [Bivariate Granger Causality] [Granger Causality...] [2009-12-23 18:23:32] [95cead3ebb75668735f848316249436a]
-   P                     [Bivariate Granger Causality] [gr causality met ...] [2009-12-28 17:04:30] [95cead3ebb75668735f848316249436a]
-   P                     [Bivariate Granger Causality] [gr causality met ...] [2009-12-28 17:09:15] [95cead3ebb75668735f848316249436a]
-   P                     [Bivariate Granger Causality] [gr causality zond...] [2009-12-28 17:13:06] [95cead3ebb75668735f848316249436a]
-   P                     [Bivariate Granger Causality] [gr causality zond...] [2009-12-28 17:14:47] [95cead3ebb75668735f848316249436a]
-   P                     [Bivariate Granger Causality] [gr causality zond...] [2009-12-28 17:16:10] [95cead3ebb75668735f848316249436a]
-   P                     [Bivariate Granger Causality] [gr causality zond...] [2009-12-28 17:18:27] [95cead3ebb75668735f848316249436a]
-   P                     [Bivariate Granger Causality] [gr causality zond...] [2009-12-28 17:19:08] [95cead3ebb75668735f848316249436a]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
2350.44
2440.25
2408.64
2472.81
2407.6
2454.62
2448.05
2497.84
2645.64
2756.76
2849.27
2921.44
2981.85
3080.58
3106.22
3119.31
3061.26
3097.31
3161.69
3257.16
3277.01
3295.32
3363.99
3494.17
3667.03
3813.06
3917.96
3895.51
3801.06
3570.12
3701.61
3862.27
3970.1
4138.52
4199.75
4290.89
4443.91
4502.64
4356.98
4591.27
4696.96
4621.4
4562.84
4202.52
4296.49
4435.23
4105.18
4116.68
3844.49
3720.98
3674.4
3857.62
3801.06
3504.37
3032.6
3047.03
2962.34
2197.82
2014.45
1862.83
1905.41
1810.99
1670.07
1864.44
2052.02
2029.6
2070.83
2293.41
2443.27
2513.17
Dataseries Y:
Download CSV
Histogram 
627
696
825
677
656
785
412
352
839
729
696
641
695
638
762
635
721
854
418
367
824
687
601
676
740
691
683
594
729
731
386
331
707
715
657
653
642
643
718
654
632
731
392
344
792
852
649
629
685
617
715
715
629
916
531
357
917
828
708
858
775
785
1006
789
734
906
532
387
991
841

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time6 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 6 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70557&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]6 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70557&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70557&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 time6 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Granger Causality Test: Y = f(X)
ModelRes.DFDiff. DFFp-value
Complete model36
Reduced model47-112.585808240383940.0155892792320968

\begin{tabular}{lllllllll}
\hline
Granger Causality Test: Y = f(X) \tabularnewline
Model & Res.DF & Diff. DF & F & p-value \tabularnewline
Complete model & 36 &  &  &  \tabularnewline
Reduced model & 47 & -11 & 2.58580824038394 & 0.0155892792320968 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70557&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]36[/C][C][/C][C][/C][C][/C][/ROW]
[ROW][C]Reduced model[/C][C]47[/C][C]-11[/C][C]2.58580824038394[/C][C]0.0155892792320968[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70557&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70557&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:

Granger Causality Test: Y = f(X)
ModelRes.DFDiff. DFFp-value
Complete model36
Reduced model47-112.585808240383940.0155892792320968






Granger Causality Test: X = f(Y)
ModelRes.DFDiff. DFFp-value
Complete model36
Reduced model47-110.6468528623386060.776762912448007

\begin{tabular}{lllllllll}
\hline
Granger Causality Test: X = f(Y) \tabularnewline
Model & Res.DF & Diff. DF & F & p-value \tabularnewline
Complete model & 36 &  &  &  \tabularnewline
Reduced model & 47 & -11 & 0.646852862338606 & 0.776762912448007 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70557&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]36[/C][C][/C][C][/C][C][/C][/ROW]
[ROW][C]Reduced model[/C][C]47[/C][C]-11[/C][C]0.646852862338606[/C][C]0.776762912448007[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70557&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70557&T=2

As an alternative you can also use a QR Code:  
QR Code


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

Granger Causality Test: X = f(Y)
ModelRes.DFDiff. DFFp-value
Complete model36
Reduced model47-110.6468528623386060.776762912448007


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 0 ; par3 = 0 ; par4 = 12 ; par5 = 1 ; par6 = 0 ; par7 = 0 ; par8 = 6 ;
Parameters (R input):
par1 = 1 ; par2 = 0 ; par3 = 0 ; par4 = 12 ; par5 = 1 ; par6 = 0 ; par7 = 0 ; par8 = 11 ;
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')