Re: [R] extended Kalman filter for survival data

From: Christos Argyropoulos <argchris_at_hotmail.com>
Date: Sat, 12 Jun 2010 05:46:19 +0300

If you mean this paper by Fahrmeir: http://biomet.oxfordjournals.org/cgi/content/abstract/81/2/317 I would recommend BayesX: http://www.stat.uni-muenchen.de/~bayesx/. BayesX interfaces with R and estimates discrete (and continuous) time survival data with penalized regression methods. If you are looking for a bona fide Bayesian survival analysis method and do not wish to spend a lot of time coming up and debugging your MCMC implementations in WinBUGS/JAGS/OpenBUGS this would be the way to go. If you are strictly after frequentist analyses then you can still run them with BayesX (look at the REML chapter in the manual).

Christos Argyropoulos

> Date: Mon, 3 May 2010 23:18:28 +0200
> From: dutangc_at_gmail.com
> To: r-help_at_r-project.org
> Subject: [R] extended Kalman filter for survival data
>
> Dear all,
>
> I'm looking for an implementation of the generalized extended Kalman filter
> for survival data, presented in this article Fahrmeir (1994) - 'dynamic
> modelling for discrete time survival data'. The same author also publish a
> Bayesian version of the algorithm 'dynamic discrete-time duration models'.
>
> The maintainer of the Survival task view advises me to take a look at
> http://cran.r-project.org/web/packages/sspir/index.html
> Unfortunately, the pkg implements "only" dynamic GLM.
>
> That's why I'm asking on this list, if someone knows a package for this
> implementation?
>
> Thanks in advance
>
> Christophe
>
>
>
> PS: the pseudo vignette of the sspir pkg can be found here
> http://www.jstatsoft.org/v16/i01/paper .
>
> --
> Christophe DUTANG
> Ph. D. student at ISFA
>
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>
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