Exit wave restoration using focus series of images has become a widely used technique to improve image resolution and interpretation. To understand the effects of the imaging approximations used, we have critically compared the specimen exit wave functions restored using the efficient linear Wiener filter, with a general nonlinear maximum likelihood method.

The objective of this paper is to provide an extension of well-known models of tarification in automobile insurance. The analysis begins by introducing a regression component in the Poisson model in order to use all available information in the estimation of the distribution. In a second step, a random variable is included in the regression component of the Poisson model and a negative binomial model with a regression component is derived. We then present our main contribution by proposing a bonus-malus system which integrates a priori and a posteriori information on an individual basis. We show how net premium tables can be derived from the model. Examples of tables are presented.