Parameter estimation for \(p\)-order random coefficient autoregressive (RCA) models based on Kalman filter (Q2337033)

Summary: In this paper we elaborate an algorithm to estimate \(p\)-order Random Coefficient Autoregressive Model (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), we have integrated a subalgorithm which calculate the theoretical autocorrelation. Simulation results demonstrate that the algorithm is viable and promising.