Asymptotic properties of estimators for autoregressive models with errors in variables
成果类型：
Article
署名作者：
Chanda, KC
刊物名称：
ANNALS OF STATISTICS
ISSN/ISSBN：
0090-5364
发表日期：
1996
页码：
423-430
关键词：
摘要：
Let {X(t), t is an element of Z} be an observable strictly stationary sequence of random variables and let X(t) = U-t + epsilon(t), where {U-t} is an AR (p) and {epsilon(t)} is a strictly stationary sequence representing errors of measurement in {X(t)}, with E{epsilon(1)} = 0. Under some broad assumptions on {epsilon(t)} We establish the consistency properties as well as the rates of convergence for the standard estimators for the autoregressive parameters computed from a set of modified Yule-Walker equations.