[R] strucchange Nyblom-Hansen Test?
buehler.daniel at web.de
Wed Oct 26 12:15:02 CEST 2011
Thank you, things seem to be clearer :-)
> Hansen extended this to the linear regression model and proposed to either
> compute one test statistic per parameter (which you can do with the "parm"
> argument of gefp) or a joint statistic for all parameters. Hansen included
> in "all" parameters also the variance,
The "parm" argument of gefp is a nice feature, but what is about the
significance level in test statistic compuation (sctest)? Is there multiple
testing correction applied or should I rather use for this case the double
max statistic as recommended below?
An excerpt from page 5 of the paper "A Unified Approach to Structural Change
Tests Based obn F Statistics, OLS Residuals, and ML Scores" (Achim Zeileis):
Hansen (1992) suggests to compute this statistic for the full process efp(t)
to test all coefficients
simultaneously and also for each component of the process (efp(t))j
(denoting the j-th component
of the process efp(t), j = 1, . . . , k) individually to assess which
parameter causes the instability.
*Note, that this approach leads to a violation of the significance level of
the procedure if no multiple
testing correction is applied.* This can be avoided if a functional is
applied to the empirical
fluctuation process which aggregates over time first yielding k independent
test statistics (see
Zeileis and Hornik 2003, for more details).
View this message in context: http://r.789695.n4.nabble.com/strucchange-Nyblom-Hansen-Test-tp3887208p3940055.html
Sent from the R help mailing list archive at Nabble.com.
More information about the R-help