We give the limiting distribution of the least squares estimator in the polynomial regression model driven by some long memory processes. We prove that with an appropriate normalization, the estimation error converges, in distribution, to a random vector which components are a mixture of...

A popular Bayesian nonparametric approach to survival analysis consists in modeling hazard rates as kernel mixtures driven by a completely random measure. In this paper we derive asymptotic results for linear and quadratic functionals of such random hazard rates. In particular, we prove central...

The paper gives a central limit theorem for symmetric statistics of exchangeable random variables using the methods in Dykin and Mandelbaum (Ann. Statist. 11, 1983) and Mandrekar and Rao (Probab. Math. Statist. 10, 1989).