Bayesian statistics represents a powerful framework for data analysis that centres on Bayes’ theorem, enabling researchers to update existing beliefs with incoming evidence. By combining prior ...

Clustering problems (including the clustering of individuals into outcrossing populations, hybrid generations, full-sib families and selfing lines) have recently received much attention in population ...

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 ...

The factor model is an important construct for both portfolio managers and researchers in modern finance. For practitioners, factor model coefficients are used to guide the construction of optimal ...

What Is A Hierarchical Models? Hierarchical models, also known as hierarchical statistical models, multilevel models or random-effects models, are tools for analysing data with a nested or grouped ...

Mike Lee receives relevant research funding from the Australian Research Council, the Australia-Pacific Science Foundation, and Flinders University. Benedict King receives funding from the Australian ...