  We propose new nonparametric accordance R\'enyi-$\alpha$ and $\alpha$-Tsallis
divergence estimators for continuous distributions. We discuss this approach
with a view to the selection model (on al\'etoire and autoregressive AR (1)).
We lestimateur used by kernel density esttimer underlying. Nevertheless, we are
able to prove that the estimators are consistent under certain conditions. We
also describe how to apply these estimators and demonstrate their effectiveness
through numerical experiments.
