Estimation in a linear model with serially correlated errors when observations are missing

Colin R Mckenzie, C. A. Kapuscinski

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

This paper compares the asymptotic efficiency of a number of two step estimators developed for estimating a static linear regression model with serially correlated errors when some observations are missing. A Monte Carlo simulation is used to illustrate the results in small samples.

Original languageEnglish
Pages (from-to)1-9
Number of pages9
JournalMathematics and Computers in Simulation
Volume44
Issue number1
Publication statusPublished - 1997 May
Externally publishedYes

Fingerprint

Correlated Errors
Asymptotic Efficiency
Linear Regression Model
Linear regression
Small Sample
Linear Model
Monte Carlo Simulation
Estimator
Observation
Monte Carlo simulation
Two-step estimator
Asymptotic efficiency
Linear regression model
Small sample

ASJC Scopus subject areas

  • Information Systems and Management
  • Control and Systems Engineering
  • Applied Mathematics
  • Computational Mathematics
  • Modelling and Simulation

Cite this

Estimation in a linear model with serially correlated errors when observations are missing. / Mckenzie, Colin R; Kapuscinski, C. A.

In: Mathematics and Computers in Simulation, Vol. 44, No. 1, 05.1997, p. 1-9.

Research output: Contribution to journalArticle

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