|
Bayesian
analysis (Foundations, Decision theory, Testing, Model
choice, Variable
selection, objective priors, restricted information inference,
approximate methods)
Computational Statistics (Random generators, ABC
algorithms, Monte
Carlo methods,
MCMC methods, Stochastic optimization)
Latent variable models (Mixtures, Hidden Markov
models, ARCH models,
Stochastic volatility, &tc.)
Applied modelling (Genetics, Astronomy, Ecology,
Econometrics, Small
Area Estimation)
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