ISSN:
1573-1375
Keywords:
extended gamma process
;
hazard rates
;
latent variables
;
Laplace transform
;
infinitely divisible distributions
Source:
Springer Online Journal Archives 1860-2000
Topics:
Computer Science
,
Mathematics
Notes:
Abstract In the context of Bayesian non-parametric statistics, the distribution of a stochastic process serves as a prior over the class of functions indexed by its sample paths. Dykstra and Laud (1981) defined a stochastic process whose sample paths can be used to index monotone hazard rates. Although they gave a mathematical description of the corresponding posterior process, numerical evaluations of useful posterior summaries were not feasible for realistic sample sizes. Here we show how a full Bayesian posterior computation is made possible by novel Monte Carlo methods that approximate random increments of the posterior process.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1007/BF00161576
Permalink
