I enjoyed your program but I'm looking to tackle a little different problem. I have a loop and I want to jump to the next iteration of the loop if a certain amount of time has past. I'm not sure how to do this. I'd appreciate any help you can provide.

01 Oct 2009

Granger Causality Test
GranTest(u,y) Tests and declares if a signal u is a cause for the second signal y, or the case is vi
Author: H. Sh. G.

Thank you for your great contribution.
Yet I have a question concerning calculating F-statistic,
the parameters for numerator and denominator as at the end of the function
are y_lag and x_lag+y_lag+1.
I read in Wikipedia which says "the simple linear model y = mx + b has p=2 ", if Wikipedia
is right, then the parameters should be "y_lag+1 and x_lag+y_lag+2"

could you please explain this in a simple way? I am quite confused.
*http://en.wikipedia.org/wiki/F-test

04 Feb 2012

Granger Causality Test
Conducts a Granger Causality test using the Bayesian Information Criterion to select lag length
Author: Chandler

This function uses Matlab function "regress" which assumes a constant term(intercept) in the linear regression and therefore violates Granger causality definition(See Granger's original paper, Econometrica 37:3 424-438, 1969).

I applied this function on two random numbers series (10 time points, lag = 2) and repeated 1000 times (every time the two series are different), and set the alpha value as 0.05. Among the 1000 tests, 400 were found to have "Granger causality"! So I think the result is not reliable.

05 Aug 2011

Granger Causality Test
Conducts a Granger Causality test using the Bayesian Information Criterion to select lag length
Author: Chandler

Dear Chandler, I have gratefully downloaded your script. How would it be possible to also include a stationarity check into the routine or would you recommend to check stationarity of the series beforehand? Many thanks, Wolfgang

18 Mar 2010

Granger Causality Test
Conducts a Granger Causality test using the Bayesian Information Criterion to select lag length
Author: Chandler

This appears to calculate the same x and y lags regardless of the actual lags present between the two vectors. In addition, the F statistic generated by the function only appears valid for specific (small) lags. The test I used involved a simple pair of sinusoids phase-shifted to various degrees with and without a small amount of Gaussian noise.

Dear Chandler
Thank you for your great contribution.
Yet I have a question concerning calculating F-statistic,
the parameters for numerator and denominator as at the end of the function
are y_lag and x_lag+y_lag+1.
I read in Wikipedia which says "the simple linear model y = mx + b has p=2 ", if Wikipedia
is right, then the parameters should be "y_lag+1 and x_lag+y_lag+2"
could you please explain this in a simple way? I am quite confused.
*http://en.wikipedia.org/wiki/F-test

5

04 Feb 2012

Granger Causality Test
Conducts a Granger Causality test using the Bayesian Information Criterion to select lag length

This function uses Matlab function "regress" which assumes a constant term(intercept) in the linear regression and therefore violates Granger causality definition(See Granger's original paper, Econometrica 37:3 424-438, 1969).
I applied this function on two random numbers series (10 time points, lag = 2) and repeated 1000 times (every time the two series are different), and set the alpha value as 0.05. Among the 1000 tests, 400 were found to have "Granger causality"! So I think the result is not reliable.

1

05 Aug 2011

Granger Causality Test
Conducts a Granger Causality test using the Bayesian Information Criterion to select lag length

Dear Chandler, I have gratefully downloaded your script. How would it be possible to also include a stationarity check into the routine or would you recommend to check stationarity of the series beforehand? Many thanks, Wolfgang

5

18 Mar 2010

Granger Causality Test
Conducts a Granger Causality test using the Bayesian Information Criterion to select lag length

This appears to calculate the same x and y lags regardless of the actual lags present between the two vectors. In addition, the F statistic generated by the function only appears valid for specific (small) lags. The test I used involved a simple pair of sinusoids phase-shifted to various degrees with and without a small amount of Gaussian noise.

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