4 search results - page 1 / 1 » Bayesian inference for nonlinear multivariate diffusion mode... |
CSDA
2008
13 years 5 months ago
2008
Diffusion processes governed by stochastic differential equations (SDEs) are a well established tool for modelling continuous time data from a wide range of areas. Consequently, t...
JCB
2006
13 years 4 months ago
2006
As postgenomic biology becomes more predictive, the ability to infer rate parameters of genetic and biochemical networks will become increasingly important. In this paper, we expl...
ICASSP
2011
IEEE
12 years 8 months ago
2011
IEEE
The Dirichlet Process Mixture (DPM) models represent an attractive approach to modeling latent distributions parametrically. In DPM models the Dirichlet process (DP) is applied es...
ISIPTA
2003
IEEE
13 years 10 months ago
2003
IEEE
Set-valued estimation offers a way to account for imprecise knowledge of the prior distribution of a Bayesian statistical inference problem. The set-valued Kalman filter, which p...