Modified Maximum Likelihood Estimation in Autoregressive Processes with Generalized Exponential Innovations

• 作者: Bernardo Lagos-álvarez Emilio Porcu Guillermo Ferreira
• 来源期刊: 统计学期刊(英文)
• 学科: 数学
• 关键词: AUTOREGRESSIVE Time Series Model MAXIMUM LIKELIHOOD MODIFIED MAXIMUM LIKELIHOOD Least SQUARES Generalized EXPONENTIAL
• 年，卷（期）: 2014,（8）
• 页码范围: 620-629
• 页数: 10页
• 分类号: O1

摘要

We consider a time series following a simple linear regression with first-order autoregressive errors belonging to the class of heavy-tailed distributions. The proposed model provides a useful generalization of the symmetrical linear regression models with independent error, since the error distribution covers both correlated innovations following a Generalized Exponential distribution. Furthermore, we derive the modified maximum likelihood (MML) estimators as an efficient alternative for estimating model parameters. Finally, we investigate the asymptotic properties of the proposed estimators. Our findings are also illustrated through a simulation study.