The following pages link to Bayesian Analysis (Q61838):
Displaying 50 items.
- Comment on article by Vernon et al. (Q5972130) (← links)
- Power-Expected-Posterior Priors as Mixtures of g-Priors in Normal Linear Models (Q5981967) (← links)
- Simulation-based Regularized Logistic Regression (Q5984583) (← links)
- Optimal shrinkage estimation of predictive densities under \(\alpha\)-divergences (Q6117926) (← links)
- Bayesian modelling of time-varying conditional heteroscedasticity (Q6117927) (← links)
- The semi-hierarchical Dirichlet process and its application to clustering homogeneous distributions (Q6117928) (← links)
- Bayesian tensor response regression with an application to brain activation studies (Q6117929) (← links)
- Spatial 3D Matérn priors for fast whole-brain fMRI analysis (Q6117931) (← links)
- Multilevel linear models, Gibbs samplers and multigrid decompositions (with discussion) (Q6117932) (← links)
- Bayesian restricted likelihood methods: conditioning on insufficient statistics in Bayesian regression (with discussion) (Q6117933) (← links)
- Robust estimation in controlled branching processes: Bayesian estimators via disparities (Q6120420) (← links)
- Bayesian estimation of correlation matrices of longitudinal data (Q6120421) (← links)
- Improving multilevel regression and poststratification with structured priors (Q6120423) (← links)
- Likelihood-free inference by ratio estimation (Q6121607) (← links)
- Heterogeneous large datasets integration using Bayesian factor regression (Q6121610) (← links)
- A Bayesian approach to modeling multivariate multilevel insurance claims in the presence of unsettled claims (Q6121611) (← links)
- Bias correction in clustered underreported data (Q6121613) (← links)
- Joint Bayesian analysis of multiple response-types using the hierarchical generalized transformation model (Q6121614) (← links)
- Scalable approximate Bayesian computation for growing network models via extrapolated and sampled summaries (Q6121615) (← links)
- Finding our way in the dark: approximate MCMC for approximate Bayesian methods (Q6121616) (← links)
- Ensemble MCMC: accelerating pseudo-marginal MCMC for state space models using the ensemble Kalman filter (Q6121617) (← links)
- Bayesian quickest detection of credit card fraud (Q6121620) (← links)
- Bayesian nonstationary and nonparametric covariance estimation for large spatial data (with discussion) (Q6121621) (← links)
- \(R^{\ast}\): a robust MCMC convergence diagnostic with uncertainty using decision tree classifiers (Q6121679) (← links)
- Error control of the numerical posterior with Bayes factors in Bayesian uncertainty quantification (Q6121680) (← links)
- Colombian women's life patterns: a multivariate density regression approach (Q6121681) (← links)
- On Bayesian inference for the extended Plackett-Luce model (Q6121684) (← links)
- Perfect sampling of the posterior in the hierarchical Pitman-Yor process (Q6121773) (← links)
- Bayesian topological learning for classifying the structure of biological networks (Q6121774) (← links)
- Quantifying observed prior impact (Q6121775) (← links)
- On a Dirichlet process mixture representation of phase-type distributions (Q6121778) (← links)
- Bayesian dependent functional mixture estimation for area and time-indexed data: an application for the prediction of monthly county employment (Q6121779) (← links)
- Bayesian concentration ratio and dissonance (Q6121780) (← links)
- Personalized dynamic treatment regimes in continuous time: a Bayesian approach for optimizing clinical decisions with timing (Q6121782) (← links)
- An ensemble EM algorithm for Bayesian variable selection (Q6121783) (← links)
- On posterior consistency of Bayesian factor models in high dimensions (Q6121784) (← links)
- The attraction Indian buffet distribution (Q6121787) (← links)
- Biclustering via semiparametric Bayesian inference (Q6121788) (← links)
- Bayesian survival tree ensembles with submodel shrinkage (Q6121789) (← links)
- Power-expected-posterior priors as mixtures of \(g\)-priors in normal linear models (Q6121976) (← links)
- Functional central limit theorems for stick-breaking priors (Q6121977) (← links)
- Informative Bayesian neural network priors for weak signals (Q6121979) (← links)
- Finite mixtures of ERGMs for modeling ensembles of networks (Q6121980) (← links)
- Bayesian sparse spiked covariance model with a continuous matrix shrinkage prior (Q6121981) (← links)
- Gaussian orthogonal latent factor processes for large incomplete matrices of correlated data (Q6121983) (← links)
- Bayesian nonparametric density autoregression with lag selection (Q6121984) (← links)
- Bayesian causal inference with bipartite record linkage (Q6121985) (← links)
- Deep Gaussian processes for calibration of computer models (with discussion) (Q6121987) (← links)
- Inverse Bayesian optimization: learning human acquisition functions in an exploration vs exploitation search task (Q6122013) (← links)
- Scalable Bayesian high-dimensional local dependence learning (Q6122014) (← links)
