Advancements in Bayesian Methods and Implementations
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portes grátis
Advancements in Bayesian Methods and Implementations
Rao, C.R.; Young, Alastair G; Srinivasa Rao, Arni S.R.
Elsevier Science & Technology
09/2022
320
Dura
Inglês
9780323952682
15 a 20 dias
1000
Descrição não disponível.
1. Fisher Information, Cramer-Rao and Bayesian Paradigm Roy Frieden 2. Compound beta binomial distribution functions Angelo Plastino 3. MCMC for GLMMS Vivekananda Roy 4. Signal Processing and Bayesian Chandra Murthy 5. Mathematical theory of Bayesian statistics where all models are wrong Sumio Watanabe 6. Machine Learning and Bayesian Jun Zhu 7. Non-parametric Bayes Stephen Walker 8. Bayesian testing Christian Robert 9. Data Analysis with humans Sumio Kaski 10. Bayesian Inference under selection G. Alastair Young 10. Variational inference or Functional horseshoe Anirban Bhattacharya 11. Generalized Bayes Ryan Martin
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Asymptotics; Bayesian GLMM; Bayesian inference; Bayesian model selection; Bayesian multiple testing; BIC; Covariance matching; Cross validation, Information criterion; Data augmentation; Dependent data; DIC; Dictionary learning; EM; Empirical risk minimization; False discovery rate; Free energy; Generalization loss; GLM; Hamiltonian Monte Carlo; Hypothesis testing; Improper priors; Inference approach; Information criterion; Learning rate; MALA; Markov chain Monte Carlo; Martingale; M-estimation; Metropolis-Hastings; Missing data; Mixed models; Mixtures; Model evaluation; Model misspecification; Monte Carlo; Monte Carlo maximum likelihood; Multiple comparison procedures; Noninformative prior; Particle-based variational inference; Posterior predictive; Prior evaluation; Prior specification; Probability matching; Pure states; Quantized compressed sensing; Riemannian geometry; Selective inference; Sparse Bayesian learning; spatial GLMM; Statistical learning; Stochastic gradient descent; Structured sparsity; Variable selection; WAIC; Wave functions; Wireless channel estimation
1. Fisher Information, Cramer-Rao and Bayesian Paradigm Roy Frieden 2. Compound beta binomial distribution functions Angelo Plastino 3. MCMC for GLMMS Vivekananda Roy 4. Signal Processing and Bayesian Chandra Murthy 5. Mathematical theory of Bayesian statistics where all models are wrong Sumio Watanabe 6. Machine Learning and Bayesian Jun Zhu 7. Non-parametric Bayes Stephen Walker 8. Bayesian testing Christian Robert 9. Data Analysis with humans Sumio Kaski 10. Bayesian Inference under selection G. Alastair Young 10. Variational inference or Functional horseshoe Anirban Bhattacharya 11. Generalized Bayes Ryan Martin
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Asymptotics; Bayesian GLMM; Bayesian inference; Bayesian model selection; Bayesian multiple testing; BIC; Covariance matching; Cross validation, Information criterion; Data augmentation; Dependent data; DIC; Dictionary learning; EM; Empirical risk minimization; False discovery rate; Free energy; Generalization loss; GLM; Hamiltonian Monte Carlo; Hypothesis testing; Improper priors; Inference approach; Information criterion; Learning rate; MALA; Markov chain Monte Carlo; Martingale; M-estimation; Metropolis-Hastings; Missing data; Mixed models; Mixtures; Model evaluation; Model misspecification; Monte Carlo; Monte Carlo maximum likelihood; Multiple comparison procedures; Noninformative prior; Particle-based variational inference; Posterior predictive; Prior evaluation; Prior specification; Probability matching; Pure states; Quantized compressed sensing; Riemannian geometry; Selective inference; Sparse Bayesian learning; spatial GLMM; Statistical learning; Stochastic gradient descent; Structured sparsity; Variable selection; WAIC; Wave functions; Wireless channel estimation
