The robust estimation for Poisson autoregressive models is studied. As a robust estimator, a minimum density power divergence estimator (MDPDE) is considered. It is shown that under regularity conditions, the MDPDE is strongly consistent and asymptotically normal. Simulation results are provided...

This paper proposes a quantile regression estimator for the diffusion parameter in diffusion processes with compound Poisson jumps. The method is based on discretely sampled observations at high frequency. We verify its consistency and exhibit its robustness to jumps through a simulation study.

In this paper, we study the robust estimation for the covariance matrix of stationary multivariate time series. As a robust estimator, we propose to use a minimum density power divergence estimator (MDPDE) designed by Basu et al. (1998). To supplement the result of Kim and Lee (2011), we employ...