The following pages link to Bayesian Analysis (Q61838):
Displaying 50 items.
- On the use of Cauchy prior distributions for Bayesian logistic regression (Q1631551) (← links)
- Sequential Bayesian analysis of multivariate count data (Q1631552) (← links)
- Bayesian analysis of RNA-Seq data using a family of negative binomial models (Q1631554) (← links)
- Efficient model comparison techniques for models requiring large scale data augmentation (Q1631557) (← links)
- Testing un-separated hypotheses by estimating a distance (Q1631558) (← links)
- Variational Hamiltonian Monte Carlo via score matching (Q1631559) (← links)
- Merging MCMC subposteriors through Gaussian-process approximations (Q1631561) (← links)
- Modeling skewed spatial data using a convolution of Gaussian and log-Gaussian processes (Q1631562) (← links)
- Bayesian cluster analysis: point estimation and credible balls (with discussion) (Q1631564) (← links)
- Prior distributions for objective Bayesian analysis (Q1631565) (← links)
- Note of correction: ``Conjugate analysis of the Conway-Maxwell-Poisson distribution'' (Q1631566) (← links)
- Posterior predictive \(p\)-values with Fisher randomization tests in noncompliance settings: test statistics vs discrepancy measures (Q1631569) (← links)
- Some aspects of symmetric Gamma process mixtures (Q1631572) (← links)
- Power-expected-posterior priors for generalized linear models (Q1631573) (← links)
- Specification of informative prior distributions for multinomial models using vine copulas (Q1631575) (← links)
- Bayesian community detection (Q1631576) (← links)
- Sampling latent states for high-dimensional non-linear state space models with the embedded HMM method (Q1631578) (← links)
- Variable selection via penalized credible regions with Dirichlet-Laplace global-local shrinkage priors (Q1631579) (← links)
- A new regression model for bounded responses (Q1631582) (← links)
- Sampling errors in nested sampling parameter estimation (Q1631585) (← links)
- Modelling and computation using NCoRM mixtures for density regression (Q1631587) (← links)
- Using stacking to average Bayesian predictive distributions (with discussion) (Q1631589) (← links)
- Big data Bayesian linear regression and variable selection by normal-inverse-gamma summation (Q1631590) (← links)
- Designing simple and efficient Markov chain Monte Carlo proposal kernels (Q1631594) (← links)
- Nonparametric Bayesian negative binomial factor analysis (Q1631595) (← links)
- Reciprocal graphical models for integrative gene regulatory network analysis (Q1631597) (← links)
- Bayesian model selection of regular vine copulas (Q1631599) (← links)
- Sequential Monte Carlo smoothing with parameter estimation (Q1631601) (← links)
- A general method for robust Bayesian modeling (Q1631602) (← links)
- The matrix-F prior for estimating and testing covariance matrices (Q1631604) (← links)
- Optimal Bayesian minimax rates for unconstrained large covariance matrices (Q1631606) (← links)
- Learning Markov equivalence classes of directed acyclic graphs: an objective Bayes approach (Q1631609) (← links)
- Bayesian spatiotemporal modeling using hierarchical spatial priors, with applications to functional magnetic resonance imaging (with discussion) (Q1631610) (← links)
- Bayesian inference and model assessment for spatial point patterns using posterior predictive samples (Q1699636) (← links)
- Bayesian two-stage design for phase II clinical trials with switching hypothesis tests (Q1699638) (← links)
- Posterior concentration rates for counting processes with Aalen multiplicative intensities (Q1699639) (← links)
- Bayesian nonparametric tests via sliced inverse modeling (Q1699640) (← links)
- The general projected normal distribution of arbitrary dimension: modeling and Bayesian inference (Q1699643) (← links)
- Hierarchical shrinkage priors for regression models (Q1699645) (← links)
- Bayesian endogenous Tobit quantile regression (Q1699646) (← links)
- Adaptive empirical Bayesian smoothing splines (Q1699648) (← links)
- Towards a multidimensional approach to Bayesian disease mapping (Q1699650) (← links)
- Estimating the marginal likelihood using the arithmetic mean identity (Q1699652) (← links)
- Adapting the ABC distance function (Q1699654) (← links)
- Bayesian estimation of principal components for functional data (Q1699656) (← links)
- Bayesian functional data modeling for heterogeneous volatility (Q1699658) (← links)
- Latent space approaches to community detection in dynamic networks (Q1699660) (← links)
- Dependent species sampling models for spatial density estimation (Q1699661) (← links)
- A hierarchical Bayesian setting for an inverse problem in linear parabolic PDEs with noisy boundary conditions (Q1699664) (← links)
- Bayesian inference for diffusion-driven mixed-effects models (Q1699666) (← links)
