A general and basic model for inference about characteristics of a finite population of distinguishable elements is presented from a subjectivistic-Bayesian point of view. A subjectivist analogue to ...

We estimate by Bayesian inference the mixed conditional heteroskedasticity model of Haas et al. (2004a Journal of Financial Econometrics 2, 211–50). We construct a Gibbs sampler algorithm to compute ...

Articulate the primary interpretations of probability theory and the role these interpretations play in Bayesian inference Use Bayesian inference to solve real-world statistics and data science ...

Scientists have quantified what draws mosquitoes to people—which could help make better, life-saving bug traps.

This paper extends the Bayesian Model Averaging framework to panel data models where the lagged dependent variable as well as endogenous variables appear as regressors. We propose a Limited ...

Infectious diseases continue to pose significant challenges to public health systems worldwide, particularly in settings where resources, surveillance ...