缺失观测值AR(1)模型的新估计

M. Issa
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引用次数: 0

摘要

本文利用普通最小二乘(OLS)方法,导出了AR(1)的参数的新形式,讨论了OLS估计量的性质,并对AR(1)提出了Youssef[18]对AR(1)的推广。采用蒙特卡罗模拟方法,对平稳和近单位根时间序列的(OLS)、Yule-Walker (YW)和修正的普通最小二乘(MOLS)进行了比较研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
New Estimator for AR (1) Model with Missing Observations
: In this paper, new form of the parameters of AR(1) with constant term with missing observations has been derived by using Ordinary Least Squares (OLS) method, Also, the properties of OLS estimator are discussed, moreover, an extension of Youssef [18]has been suggested for AR(1) with constant with missing observations. A comparative study between (OLS), Yule-Walker (YW) and modification of the ordinary least squares (MOLS) is considered in the case of stationary and near unit root time series, using Monte Carlo simulation.
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