Invited Speaker
Prof. Benmoumen Mohammed
LaMSD, Department of Mathematics, Faculty of Sciences, Mohammed the First University, Oujda, MoroccoSpeech Title: Parameter Estimation and Strong Consistency for p-Order Random Coefficient Autoregressive (RCA) process Based on Kalman Filter
Abstract: In this paper we elaborate an algorithm to estimate p-order Random Coefficient Autoregressive process (RCA(p)) parameters. This algorithm combines quasi-maximum likelihood method, the Kalman filter, and the simulated annealing method. In the aim to generalize the results found for RCA(1) (see Benmoumen and al 2013), we have integrated a sub-algorithm which calculates the theoretical autocorrelation. We also investigate the strong consistency of the quasi-maximum likelihood estimators derived through the Kalman filter for stationary random coefficient autoregressive (RCA) process (Benmoumen and Salhi 2021). Simulation results demonstrate that the algorithm is viable and promising.