Re: [R] efpFunctional construction (strucchange package)

2011-11-12 Thread bonda
Unfortunately, I couldn't find neither this source file, nor function wmax().
Was it any old version of strucchange? There are only files strucchange.R,
strucchange.rdb and strucchange.rdx in directory \strucchange\R.

Best,
Julia

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[R] efpFunctional construction (strucchange package)

2011-11-10 Thread bonda
Hello,

to understand better how efpFunctional works, I'm trying to construct my own
functionals. But concerning already existing functionals I have some
questions. With maxBB it is clear:

functional = list(comp = function(x) max(abs(x)), time = max),

with rangeBB:

functional = list(time = function(x) max(x)-min(x), comp = max),

with meanL2BB, if I understood correctly:

functional = list(comp = function(x) sum(x^2), time = mean).

How can I write a functional supLM(from=..., to=...)?

Thank you in advance.

Julia

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Re: [R] nproc parameter in efpFunctional

2011-11-07 Thread bonda
Thank you very much, it works now!
Best regards,
J

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Re: [R] nproc parameter in efpFunctional

2011-11-04 Thread bonda
The 2006 CSDA paper is really very informative, perhaps, I'm trying to
understand the things lying beyond. If we have e.g. k=3, then taking nproc=3
for the functional maxBB we get a critical value (boundary)

maxBB$computeCritval(0.05,nproc=3)
[1] 1.544421,

and this for nproc=NULL (Bonferroni approximation) will be

maxBB$computeCritval(0.05)
[1] 1.358099.

Aggregating 3 Brownian bridges first over components, we obtain time series
process. Now, we wonder if maximum value of the process (aggregation over
time) lies over boundary. Which boundary - 1.544421 or 1.358099 - should one
take? They look too different and, for instance, lead to unfair computing
of empirical size (as rejection rate of null hypothesis) or empirical power
(as acception rate of alternative). 




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Re: [R] nproc parameter in efpFunctional

2011-11-03 Thread bonda
Thank you. I've understood, that it should be k (number of parameters)
separate Brownian bridges. 
Is it possible, to get such separated/disaggregated processes also in
function efp()? (one can take gefp(..., family=gaussian), or construct by
myself residuals(lm.model)*X, but still interesting). And on the contrary,
how can I get an aggregated Brownian bridge path for all parameters
together, similar to efp()$process? It is made in plot.gefp, but only for
graphical visualization...
Thank you in advance!
Julia

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[R] nproc parameter in efpFunctional

2011-11-02 Thread bonda
Hello all,
could anyone explain the exact meaning of parameter nproc? Why different
values of nproc give so different critical values, i.e.

meanL2BB$computeCritval(0.05,nproc=3)
[1] 0.9984853
meanL2BB$computeCritval(0.05,nproc=1)
[1] 0.4594827

The strucchange-package description gives integer specifying for which
number of processes Brownian motions should be simulated - do I need
nproc-dimensional Brownian bridge?

Thank you in advance!
Julia

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Re: [R] gefp() boundaries?

2011-10-07 Thread bonda
Well, I am still confused... shouldn't the made-by-hands-process (correctly
constructed, of course) and the gefp()-process be similar? For the case of
efp()-process it has been worked, at least... Besides, I'd like to know:
1) if I have the gefp()-process (scaled to unit interval [0;1]), can I get
the unscaled one for the interval [0;n]?
2) is it possible to define a type of the score process like this was in
efp()? I could find that neither in ?gefp, nor in CSDA-paper-2006.
The example was bad and incorrect, the another one:

data(BostonHomicide)

gprocess - gefp(homicides ~ ahomicides25, family = poisson, data =
BostonHomicide);

my.model - glm(homicides ~ ahomicides25, family = poisson, data =
BostonHomicide);
J - vcov(my.model);
J.sqrinv - solve(sqrtm(J))/n;
my.psi - estfun(my.model);
my.process - apply(as.matrix(my.psi), 2, cumsum)%*%t(J.sqrinv)/sqrt(n);

Regards,
Julia





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Re: [R] gefp() boundaries?

2011-10-06 Thread bonda
Thank you very much for the answer. If I take Poisson model and follow
Generalized M-fluctuation tests for parameter instability, A. Zeileis and
K. Hornik, Statistica Neerlandica (2007) Vol. 61, N. 4, p. 500-501 (section
4.3):

data(Boston)
n - 506;
my.X - as.matrix(cbind(1, Boston[crim], Boston[age])); 
my.model - glm(tax ~ crim + age, family = poisson, data = Boston);
my.psi - estfun(my.model);
my.mu - fitted(my.model);
J - sum(my.mu*my.X%*%t(my.X))/n;
my.process - apply(as.matrix(my.psi), 2, cumsum)/sqrt(J*n);

gprocess - gefp(tax ~ crim + age, family = poisson, data=Boston);

then my.process and gprocess$process have to be the same? 

Best regards,
Julia

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[R] gefp() boundaries?

2011-10-04 Thread bonda
Hello all,

I have the following two questions: 1) how can I get the values of
boundaries for fluctuation process gefp(), for functionals maxBB, meanL2BB,
etc? 2) how can I get fragments of gefp()-process, e.g., if I have n=200
observations, i=1,2,...,200, and need gefp()[50:100], i.e. from i=50 till
i=100?

Thank you in advance,
Julia

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[R] One-sided CUSUM / MOSUM Tests?

2010-09-27 Thread bonda

Dear R-help list members,

I have the following question concerning the strucchange()-package: is  
it possible to get the boundaries for one-sided (upper / lower) CUSUM  
and MOSUM tests?


Thank you in advance.

Julia

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