A Minimum Distance Estimator for First-Order Autoregressive Processes
The Annals of Statistics · 1986 · Volume 14 · Issue 3
Abstract
In this paper we construct a class of minimum distance Cramer-von Mises-type estimators for the parameter in the first-order stationary autoregressive time series. The estimator is proved to be asymptotically normal under appropriate assumptions. The proofs involve some results of independent interest.
Keywords
62L10, bounded functionals on $L_2$-spaces, conditional expectation, Lipschitz condition, Randomly weighted empirical processes, stationary and ergodic processes
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