Re: [R] R strucchange question: recursive-based CUSUM
Achim Zeileis wrote: Julia: I'm trying now to apply the package strucchange to see whether there is a structural change in linear regression. I have noted the following problem that arises in my case with recursive-based CUSUM: generic function recresid() in efp() generates an error, since (probably) it cannot compute the inverse matrix of (X^(i-1)^T)*(X^(i-1)) at each step (i-1), because the matrix (X^(i-1)^T)*(X^(i-1)) does not have full rank for all i (X consists of dummy variables). Does any solution of this problem exist (for example, to replace the ordinary inverse by the generalised inverse, ginv())? The 1-step-ahead prediction error is well-defined even if there are rank deficiencies. For example, using lm.fit() will automatically alias coefficients that are not identified. The reason why recresid() doesn't use this is that it employs a more efficient updating algorithm. If you need to investigate the recursive CUSUM test, you could hack recresid() and use the slower but more robust implementation based on lm.fit(). Personally, however, I would recommend to use a different test. In most situations (unless the break occurs very early in the sample), there are more powerful methods than the recursive CUSUM test. hth, Z Thanks a lot for detailed answer, I'll try to implement this in Rec-CUSUM () (and other tests as well). MfG, Julia __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] R strucchange question: recursive-based CUSUM
Hello R users: I'm trying now to apply the package strucchange to see whether there is a structural change in linear regression. I have noted the following problem that arises in my case with recursive-based CUSUM: generic function recresid() in efp() generates an error, since (probably) it cannot compute the inverse matrix of (X^(i-1)^T)*(X^(i-1)) at each step (i-1), because the matrix (X^(i-1)^T)*(X^(i-1)) does not have full rank for all i (X consists of dummy variables). Does any solution of this problem exist (for example, to replace the ordinary inverse by the generalised inverse, ginv())? Thank you in advance for your help! Julia __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] R strucchange question: recursive-based CUSUM
Julia: I'm trying now to apply the package strucchange to see whether there is a structural change in linear regression. I have noted the following problem that arises in my case with recursive-based CUSUM: generic function recresid() in efp() generates an error, since (probably) it cannot compute the inverse matrix of (X^(i-1)^T)*(X^(i-1)) at each step (i-1), because the matrix (X^(i-1)^T)*(X^(i-1)) does not have full rank for all i (X consists of dummy variables). Does any solution of this problem exist (for example, to replace the ordinary inverse by the generalised inverse, ginv())? The 1-step-ahead prediction error is well-defined even if there are rank deficiencies. For example, using lm.fit() will automatically alias coefficients that are not identified. The reason why recresid() doesn't use this is that it employs a more efficient updating algorithm. If you need to investigate the recursive CUSUM test, you could hack recresid() and use the slower but more robust implementation based on lm.fit(). Personally, however, I would recommend to use a different test. In most situations (unless the break occurs very early in the sample), there are more powerful methods than the recursive CUSUM test. hth, Z __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
