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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, 15 Dec 2010 16:54:41 +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/15/t1292432090lej43rulxacn6wu.htm/, Retrieved Fri, 03 May 2024 10:32:08 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=110574, Retrieved Fri, 03 May 2024 10:32:08 +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)
-     [Pearson Correlation] [Paper Pearson Cor...] [2010-12-15 15:20:07] [d59201e34006b7e3f71c33fa566f42b3]
- RMPD    [Bivariate Granger Causality] [Paper Bivariate G...] [2010-12-15 16:54:41] [f38914513f1f4d866974b642cdd0baea] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
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:
Download CSV
Histogram 
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

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 4 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110574&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]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110574&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110574&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 time4 seconds
R Server'George Udny Yule' @ 72.249.76.132






Granger Causality Test: Y = f(X)
ModelRes.DFDiff. DFFp-value
Complete model53
Reduced model54-10.2425623534366210.624395687522552

\begin{tabular}{lllllllll}
\hline
Granger Causality Test: Y = f(X) \tabularnewline
Model & Res.DF & Diff. DF & F & p-value \tabularnewline
Complete model & 53 &  &  &  \tabularnewline
Reduced model & 54 & -1 & 0.242562353436621 & 0.624395687522552 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110574&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]53[/C][C][/C][C][/C][C][/C][/ROW]
[ROW][C]Reduced model[/C][C]54[/C][C]-1[/C][C]0.242562353436621[/C][C]0.624395687522552[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110574&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110574&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 model53
Reduced model54-10.2425623534366210.624395687522552






Granger Causality Test: X = f(Y)
ModelRes.DFDiff. DFFp-value
Complete model53
Reduced model54-11.569759440013740.215741695019565

\begin{tabular}{lllllllll}
\hline
Granger Causality Test: X = f(Y) \tabularnewline
Model & Res.DF & Diff. DF & F & p-value \tabularnewline
Complete model & 53 &  &  &  \tabularnewline
Reduced model & 54 & -1 & 1.56975944001374 & 0.215741695019565 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=110574&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]53[/C][C][/C][C][/C][C][/C][/ROW]
[ROW][C]Reduced model[/C][C]54[/C][C]-1[/C][C]1.56975944001374[/C][C]0.215741695019565[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=110574&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=110574&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 model53
Reduced model54-11.569759440013740.215741695019565


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 12 ;
Parameters (R input):
par1 = 1 ; par2 = 2 ; par3 = 0 ; par4 = 12 ; par5 = 1 ; par6 = 2 ; par7 = 0 ; par8 = 1 ;
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')