A superharmonic prior for the autoregressive process of the second-order

The Bayesian estimation of the spectral density of the AR(2) process is considered. We propose a superharmonic prior on the model as a non-informative prior rather than the Jeffreys prior. Theoretically, the Bayesian spectral density estimator based on it dominates asymptotically the one based on the Jeffreys prior under the Kullback-Leibler divergence. In the present article, an explicit form of a superharmonic prior for the AR(2) process is presented and compared with the Jeffreys prior in computer simulation. Copyright 2008 The Authors