Bayesian inference of petrophysical properties with generative spectral induced polarization models

Bayesian Inference for Spatial Beta Generalized Linear Mixed Models

In some applications, the response variable assumes values in the unit interval. The standard linear regression model is not appropriate for modelling this type of data because the normality assumption is not met. Alternatively, the beta regression model has been introduced to analyze such observations. A beta distribution represents a flexible density family on (0, 1) interval that covers symm...

on some bayesian statistical models in actuarial science with emphasis on claim count

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Variational Bayesian learning of generative models

Full Bayesian inference with hazard mixture models

Bayesian nonparametric inferential procedures based on Markov chain Monte Carlo marginal methods typically yield point estimates in the form of posterior expectations. Though very useful and easy to implement in a variety of statistical problems, these methods may suffer from some limitations if used to estimate non-linear functionals of the posterior distribution. The main goal is to develop a...

Bayesian Inference with Probability Matrix Decomposition Models

Probability Mcatrix Decompositioni models mtay bve uised to model observed binary associations between two sets of elements. More specifically, to explain observed associations betweeni two elements, it is assumed that B laitent Bernoulli variables are realized for each element and that these variables are subsequently mapped into an observed data point accordingg to a prespecijied dererministi...