[R] R strucchange question: recursive-based CUSUM

[Julia Bondarenko]

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