[Developers] FW: seminar on INLA

[dave fournier]

On 13-07-24 12:02 PM, Mark Maunder wrote:

Hans reminded me that we had done a comparison of ADMB with this 
software for a spatial model.

 From my point of view the most important aspect of this is the 
flexibility of ADMB which enables one
to easily modify the model (after the initial comparative difficulty of 
writing the first model code of course)
  to include various extra structure (in this case a mixture distribution),
something you can not do with the INLA software so far as I know.

It is fairly typical of the R packages, that while they allow one to do 
a superficial analysis quickly,
they are inflexible and become a trap for the user.

      Dave










> *From:*Richard Methot - NOAA Federal [mailto:richard.methot at noaa.gov]
> *Sent:* Wednesday, July 24, 2013 11:35 AM
> *To:* Mark Maunder; Jim Ianelli - NOAA Federal; James Thorson - NOAA 
> Federal; Allan Hicks - NOAA Federal; Ian Taylor - NOAA Federal; Athol 
> Whitten
> *Subject:* seminar on INLA
>
> Dr. Janine Illian from the Centre for Research into Ecological and
> Environmental Modelling (CREEM) at the University of St. Andrews, UK
> will be visiting next week and has kindly agreed to give a NMML seminar
> (NMML conference room, Wednesday, July 31, at noon). I'll send out an
> email reminder next week, but hope you can join us. As Dr. Illian's
> topic is not limited to marine mammal applications, please feel free to
> forward this announcement to other NMFS/AFSC scientists who may be
> interested.
>
> FITTING COMPLEX MODELS IN INLA -- DEVELOPMENTS AND EXTENSIONS
>
> Integrated nested Laplace approximation (INLA) may be used to fit a
>
> large class of (complex) statistical models. While MCMC methods use
>
> stochastic simulations for estimation, integrated nested Laplace
>
> approximation (INLA) is based on deterministic approximations where
>
> there are no convergence issues. INLA is a very accurate and
>
> computationally superior alternative to MCMC and may be used to fit a
>
> large class of models, latent Gaussian models. Since INLA is fast,
>
> complex modelling has become greatly facilitated and has also become
>
> more accessible to non-specialists. In addition, due to the fact that
>
> the fitting approach is embedded in a large and general class of
>
> statistical models, very general types of models may be considered. This
>
> allows us a lot more flexibility in the choice of model than previously
>
> -- and hence the models to capture interesting aspects of the data and
>
> consequently the system they are relevant for. In the context of spatial
>
> statistics, for example, we can now fit models to spatial point patterns
>
> of high dimensionality, replicated point patterns, hierarchically marked
>
> point patterns etc. In many cases, analysing these data sets with MCMC
>
> approaches would be very cumbersome and computationally prohibitive. The
>
> INLA-methodology has been implemented in C, and the associated numerical
>
> calculations and algorithms rely on an efficient implementation of
>
> numerical procedures for Gaussian Markov random fields (GMRF), in
>
> particular the algorithms in the C-library GMRFLib. However, most users
>
> do not need to worry about this, as the INLA-methodology has been made
>
> accessible through a user-friendly R-library, R-INLA, described and
>
> available for download at www.r-inla.org <http://www.r-inla.org>. 
> Specifying and fitting models
>
> using R-INLA is just as easy as applying standard routines in R, for
>
> example fitting generalised linear models, and it also provides great
>
> flexibility with regard to the models that may be fitted. In order to
>
> illustrate INLA's versatility I will discuss a range of spatial and
>
> non-spatial examples and present a number of recent developments. This
>
> concerns generalisations of the methodology as well as new functionality
>
> within the R-INLA library.
>
> -- 
> *Richard D. Methot Jr. Ph.D.*
> /NOAA Fisheries - //Science Advisor for Stock Assessments/
>
> Office: 206-860-3365
> Mobile: 301-787-0241
>
>
>
> _______________________________________________
> Developers mailing list
> Developers at admb-project.org
> http://lists.admb-project.org/mailman/listinfo/developers

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