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Bayesian inference on dependence in multivariate longitudinal data
Cholesky decomposition covariance matrix moment-matching oxidative stress random effects shrinkage prior.
2012/9/17
In many applications, it is of interest to assess the dependence structure in multivariate longitudinal data. Discovering such dependence is challenging
due to the dimensionality involved. By concate...
Robust Bayesian inference of networks using Dirichlet t-distributions
Bayesian inference Dirichlet process graphical model Markov chain Monte Carlo t-distribution.
2012/9/18
Bayesian graphical modeling provides an appealing way to obtain uncertainty esti-mates when inferring network structures, and much recent progress has been made for Gaussian models. These models have ...
Bayesian inference with rescaled Gaussian process priors
Rate of convergence Bayesian inference nonparametric density estimation nonparametric regression classification
2009/9/16
We use rescaled Gaussian processes as prior models for functional parameters in nonparametric statistical models. We show how the rate of contraction of the posterior distributions depends on the scal...
On adaptive Bayesian inference
Adaptation rate of convergence posterior distribution density function log spline density
2009/9/16
We study the rate of Bayesian consistency for hierarchical priors consisting of prior weights on a model index set and a prior on a density model for each choice of model index. Ghosal, Lember and Van...