In additive models the problem of variable selection is strongly linked to the choice of the amount of smoothing used for components that represent metrical variables. Many software packages use separate toolsto solve the different tasks of variable selection and smoothing parameter choice. The...

This paper presents the construction of a particle filter, which incorporates elements inspired by genetic algorithms, in order to achieve accelerated adaptation of the estimated posterior distribution to changes in model parameters. Specifically, the filter is designed for the situation where...

In this paper, a robustness of Vector Auto-Regressive (VAR) models parameter will be estimated by using genetic algorithm (GA) on outliers detection. Least Square (LS) estimator has been adopted in GA term to estimate a robust parameters of the VAR models were represented by chromosomes in GA's...