losses forecasting

Forecasting Actuarial Processes with Generalized Linear Models

The method for statistical data analysis in insurance based on application of generalized linear models is studied. These models are extension of linear regression when distribution of random variable can differ from normal however belongs to the class of elliptical distributions. The model constructed can be linear or non-linear (for example, logit or probit). For parameters estimation of the models proposed the generalized least squares (GLS) or the Markov chain Monte Carlo methods are used.