MODEL-FITTING FOR CONTINUOUS-TIME STATIONARY-PROCESSES FROM DISCRETE-TIME DATA

被引：7

作者：

LII, KS ^{[1
]}

MASRY, E ^{[1
]}

机构：

[1] UNIV CALIF SAN DIEGO,LA JOLLA,CA 92093

来源：

JOURNAL OF MULTIVARIATE ANALYSIS | 1992年 / 41卷 / 01期

关键词：

PARAMETRIC SPECTRAL ESTIMATION OF CONTINUOUS-TIME PROCESSES; STATIONARY POINT PROCESSES; CONSISTENCY; ASYMPTOTIC NORMALITY;

D O I：

10.1016/0047-259X(92)90057-M

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

Let X = {X(t), -∞<t<∞} be a continuous-time stationary process with spectral density φX(λ; θ), where θ is a vector of unknown parameters. Let {τk} be a stationary point process on the real line which is independent of X. The identifiability and the estimation of θ from the discrete-time observation {X(τk), τk} are considered. The consistency of appropriate estimates θT as the time T a ̊∞ is extablished and a central limit theorem for θT is given. © 1992.

引用

页码：56 / 79

页数：24

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