On Tue, 11 May 2010, RATIARISON Eric wrote:
Hi,
I think my "meat"function is wrong.
Yes.
But the "estfun(resMaxlik)" doesn't work;
Because you haven't supplied one.
It's as I wrote in my previous mails: You need to write a bread() and an
estfun() method as specified in my previous mail. Details are in the
sandwich vignette I already pointed you to. The meat() function does not
have to be modified.
Z
Error message :
"Erreur dans UseMethod("estfun") :
pas de méthode pour 'estfun' applicable pour un objet de classe "c('maxLik', 'maxim',
'list')""
-----Message d'origine-----
De : RATIARISON Eric
Envoyé : mardi 11 mai 2010 11:47
À : 'Arne Henningsen'; Achim Zeileis; r-help@r-project.org; Ott-Siim Toomet
Objet : RE: [R] Robust SE & Heteroskedasticity-consistent estimation
Thank you all of you,;
I submit you my case:
( Pseudo likehood for exponential family with offset )
loglik <- function(param) {
b<-param
m=as.vector(of+z%*%b)
ll <- sum(v*m-exp(m)) }
gradlik <- function(param) {
b<-param
m=as.vector(of+z%*%b)
gg<-(v-exp(m))*z }
hesslik <- function(param) {
b<-param
m=as.vector(of+z%*%b)
hh <- -t(exp(m)*z)%*%z }
resMaxlik <-
maxLik(loglik,grad=gradlik,hess=hesslik,start=sc,method="nr",tol=1e-4);
n<-NROW(v)
k<-NROW(resMaxlik$estimate)
meat <-function(obj,nrow,npar,adjust=FALSE,...)
{ psi<-obj$gradient
k<-npar
n<-nrow
rval<-crossprod(as.matrix(psi))/n
if (adjust) rval <- n/(n-k)*rval
rval
}
M<-as.vector(meat(resMaxlik,n,k))
B <-as.matrix(ginv(resMaxlik$hessian))
vcovhc=B*M*B
#new standard errors
coeftest(resMaxlik,vcov.=vcovhc)
do you think it's sound good ?
-----Message d'origine-----
De : Arne Henningsen [mailto:arne.henning...@googlemail.com]
Envoyé : mardi 11 mai 2010 08:25
À : Achim Zeileis; RATIARISON Eric; r-help@r-project.org; Ott-Siim Toomet
Objet : Re: [R] Robust SE & Heteroskedasticity-consistent estimation
On 11 May 2010 00:52, Achim Zeileis <achim.zeil...@uibk.ac.at> wrote:
On Mon, 10 May 2010, RATIARISON Eric wrote:
I'm using maxlik with functions specified (L, his gradient & hessian).
Now I would like determine some robust standard errors of my estimators.
So I 'm try to use vcovHC, or hccm or robcov for example
but in use one of them with my result of maxlik, I've a the following
error message :
Erreur dans terms.default(object) : no terms component
Is there some attributes to give to maxlik objet for "fitting" the call
of vcovHC?
This is discussed in
vignette("sandwich-OOP", package = "sandwich")
one of the vignettes accompanying the "sandwich" package that provides the
vcovHC() function. At the very least, you need an estfun() method which
extracts the gradient contributions per observation. Then you need a bread()
function, typically based on the observed Hessian. Then you can compute the
basic sandwich() estimators.
Is it possible to implement the estfun() method and the bread()
function in the maxLik package so that vcovHC() can be easily used by
all users of the maxLik package? If yes: should we (Eric, Achim, Ott,
Arne) implement this feature together?
/Arne
--
Arne Henningsen
http://www.arne-henningsen.name
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