For exchangeable data, mixture models are an extremely useful tool for density estimation
due to their attractive balance between smoothness and flexibility. When additional …

In the context of predicting future claims, a fully Bayesian analysis–one that specifies a
statistical model, prior distribution, and updates using Bayes's formula–is often viewed as …

This paper proposes a new adaptive approach called adaptive mean (ADM) that combines
the strengths of trimming and winsorization to minimize the mean square error (MSE). ADM …

Predicting insurance losses is an eternal focus of actuarial science in the insurance sector.
Due to the existence of complicated features such as skewness, heavy tail, and multi …

The method of credibility theory plays a critical role in various research areas of actuarial
science. Among others, the hypothetical mean and process variance are two quantities that …

In actuarial practice, the modeling of total losses tied to a certain policy is a nontrivial task
due to complex distributional features. In the recent literature, the application of the Dirichlet …

The prediction of future insurance claims based on observed risk factors, or covariates, help
the actuary set insurance premiums. Typically, actuaries use parametric regression models …

Using the Health Care Cost Institute data (approximately 47 million members over seven
years), we examine how to best predict which members will be high-cost next year. We find …

The classical credibility theory is a cornerstone of experience rating, especially in the field of
property and casualty insurance. An obstacle to putting the credibility theory into practice is …

Ekonometrik analizlerde klasik yaklaşıma bir alternatif olarak Bayesyen yaklaşımın sıklıkla
kullanıldığı görülmektedir. Bayesyen yaklaşım, klasik yaklaşımdan farklı olarak rastgele …