Abstract Details
|
Activity Number:
|
396
|
|
Type:
|
Invited
|
|
Date/Time:
|
Tuesday, August 6, 2013 : 2:00 PM to 3:50 PM
|
|
Sponsor:
|
Section on Statistics and the Environment
|
| Abstract - #307317 |
|
Title:
|
Bayesian Computing with R-INLA: Some Recent Developments
|
|
Author(s):
|
Håvard Rue*+
|
|
Companies:
|
NTNU
|
|
Keywords:
|
GMRF ;
INLA ;
SPDE ;
R-INLA
|
|
Abstract:
|
In this talk I will discuss some recent developments for Bayesian computation within the R-INLA package (www.r-inla.org). The R-INLA package provides an implementation of approximate Bayesian inference for latent Gaussian models based on nested Laplace approximations (Rue, Martino, Chopin, 2009). Continuously indexed spatial models in this package are derived from stochastic partial differential equations (SPDEs). The SPDE approach introduced by Lindgren, Rue and Lindstrom (2011) showed how some Gaussian fields can be represented (numerically) as a Gaussian Markov Random Field (GMRF), which allow for faster computations. The SPDE approach generalise naturally to non-stationary fields and fields on manifolds.
|
Authors who are presenting talks have a * after their name.
Back to the full JSM 2013 program
|
2013 JSM Online Program Home
For information, contact jsm@amstat.org or phone (888) 231-3473.
If you have questions about the Continuing Education program, please contact the Education Department.
The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.
Copyright © American Statistical Association.