If I try the breakpoints() function (strucchange package) with a minimum
segment size = the number of regressors, there appears the following error
message:
"minimum segment size must be greater than the number of regressors"
According to the documentation:
"breakpoints implements the algorithm de
Achim Zeileis-4 wrote
>
>
> The reason for the various approaches is that efp() was always confined to
> the linear model and gefp() then extended it to arbitrary estimating
> function-based models. And for the linear model this provides the option
> of treating the variance of a nuisance par
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
Thanks a lot for your immediate help and detailed explanation!
About one thing I'm not quite clear:
When the default fit = glm in gefp() is used:
sctest(gefp(Employed ~ Year + GNP.deflator + GNP + Armed.Forces, data =
longley, fit = lm), functional = meanL2BB)
is this then the original Nyblom's
I want to apply Nyblom-Hansen test with the strucchange package, but I don't
know how is the correct way and what is the difference between the following
two approaches (leeding to different results):
data("longley")
# 1. Approach:
sctest(Employed ~ Year + GNP.deflator + GNP + Armed.Forces, data
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