Journal of Time Series Analysis

First‐Order Autoregressive Processes with Heterogeneous Persistence

Journal Article

Abstract.We propose a semi‐nonparametric method of identification and estimation for Gaussian autoregressive processes with stochastic autoregressive coefficients. The autoregressive coefficient is considered as a latent process with either a moving average or regime switching representation. We develop a consistent estimator of the distribution of the autoregressive coefficient based on nonlinear canonical decomposition of the observed process. The approach is illustrated by simulations.

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