ISSN:
0885-6125
Schlagwort(e):
Bayesian inference
;
graphical models
;
Bayes factor
;
marginal likelihood
;
hidden Markov models
;
latent variable models
Quelle:
Springer Online Journal Archives 1860-2000
Thema:
Informatik
Notizen:
Abstract Maximum a posteriori optimization of parameters and the Laplace approximation for the marginal likelihood are both basis-dependent methods. This note compares two choices of basis for models parameterized by probabilities, showing that it is possible to improve on the traditional choice, the probability simplex, by transforming to the 'softmax' basis.
Materialart:
Digitale Medien
URL:
http://dx.doi.org/10.1023/A:1007558615313