A0785
Title: Revisiting Poisson autoregressive models: Structure and statistical inference
Authors: Dong Li - Tsinghua University (China) [presenting]
Abstract: The first-order stationary Poisson autoregression (PAR) is one of the most classical count time series models and has been widely studied. However, few researchers pay attention to nonstationary PAR. PAR is revisited, and some novel results are provided on asymptotical behaviors of the intensity process under nonstationarity. Further, the maximum likelihood estimation is considered in a unified framework of stationary and nonstationary cases, and its asymptotics are established. Monte Carlo simulation studies are conducted to assess the finite-sample performance of the MLE.
