Journal of the Royal Statistical Society. Series A (Statistics in Society), Vol. 180, No. 4 (OCTOBER 2017), pp. 1191-1209 (19 pages) Area level models, such as the Fay–Herriot model, aim to improve ...

Discover how credibility theory helps actuaries use historical data to estimate risks and set insurance premiums; learn how ...

The Annals of Applied Statistics, Vol. 8, No. 2 (June 2014), pp. 852-885 (34 pages) Poverty maps are used to aid important political decisions such as allocation of development funds by governments ...

Bayesian estimation methods form a dynamic branch of statistical inference, utilising Bayes’ theorem to update probabilities in light of new evidence. This framework combines prior knowledge with ...

Bayesian estimation and maximum likelihood methods represent two central paradigms in modern statistical inference. Bayesian estimation incorporates prior beliefs through Bayes’ theorem, updating ...

When estimating DSGE models, the number of observable economic variables is usually kept small, and it is conveniently assumed that DSGE model variables are perfectly measured by a single data series.

Bayesian networks, also known as Bayes nets, belief networks, or decision networks, are a powerful tool for understanding and reasoning about complex systems under uncertainty. They are essentially ...