Asymptotics for the random coefficient first-order autoregressive model with possibly heavy-tailed innovations

作者：Fu, Ke-Ang^*; Fu, Xiaoyong

来源：Journal of Computational and Applied Mathematics, 2015, 285: 116-124.

DOI：10.1016/j.cam.2015.02.020

• Asymptotic normality
• Conditional least squares estimator
• Domain of attraction of the normal law
• Random coefficient AR(1)
• Self-normalization

Consider a random coefficient AR(1) model, X-t = (rho(n) + phi(n))Xt-i + u(t), where {rho(n,) n >= 1} is a sequence of real numbers, {phi(n), n >= 1} is a sequence of random variables, and the innovations of the model form a sequence of i.i.d.random variables belonging to the domain of attraction of the normal law. By imposing some weaker conditions, the conditional least squares estimato

• 出版日期2015-9
• 单位浙江工商大学