Pages that link to "Item:Q1623576"

The following pages link to On the use of marginal posteriors in marginal likelihood estimation via importance sampling (Q1623576):

Displaying 23 items.

• Bayesian inference for structural vector autoregressions identified by Markov-switching heteroskedasticity (Q97969) (← links)
• Pitfalls of estimating the marginal likelihood using the modified harmonic mean (Q500578) (← links)
• Improving power posterior estimation of statistical evidence (Q746315) (← links)
• A new Monte Carlo method for estimating marginal likelihoods (Q1631546) (← links)
• Efficient model comparison techniques for models requiring large scale data augmentation (Q1631557) (← links)
• Bayes factor covariance testing in item response models (Q1695737) (← links)
• Statistical inference in efficient production with bad inputs and outputs using latent prices and optimal directions (Q1753050) (← links)
• A comparative study of Monte Carlo methods for efficient evaluation of marginal likelihood (Q1927121) (← links)
• Bayesian analysis of static and dynamic Hurst parameters under stochastic volatility (Q2066041) (← links)
• Bayesian updating and marginal likelihood estimation by cross entropy based importance sampling (Q2106964) (← links)
• Inflated density ratio and its variation and generalization for computing marginal likelihoods (Q2131900) (← links)
• Computing marginal likelihoods via the Fourier integral theorem and pointwise estimation of posterior densities (Q2172117) (← links)
• Bounded rationality and thick frontiers in stochastic frontier analysis (Q2178102) (← links)
• Estimating marginal likelihoods from the posterior draws through a geometric identity (Q2213361) (← links)
• Modeling dependence structures for response times in a Bayesian framework (Q2331189) (← links)
• Thermodynamic Bayesian model comparison (Q2361465) (← links)
• Estimating marginal likelihoods for mixture and Markov switching models using bridge sampling techniques* (Q3156190) (← links)
• Scalable Bayesian Regression in High Dimensions With Multiple Data Sources (Q3391441) (← links)
• Note on posterior inference for the Bingham distribution (Q5160234) (← links)
• Marginal likelihood estimation from the Metropolis output: tips and tricks for efficient implementation in generalized linear latent variable models (Q5219477) (← links)
• Computing Marginal Likelihoods via Posterior Sampling (Q5415865) (← links)
• Estimating Monotone Concave Stochastic Production Frontiers (Q6620958) (← links)
• Hierarchical multivariate directed acyclic graph autoregressive models for spatial diseases mapping (Q6628615) (← links)