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1998•Unpublished venueRequires access

Asymptotic Equivalence of Ordinary Least Squares and Generalized Least Squares with Trending Regressors and Stationary Autoregressive Disturbances

Walter Krämer

Open publisher page 5 citations

Abstract

This note generalizes previous results on the asymptotic equivalence of Ordinary and Generalized Least Squares estimates in Linear Regression models with trending data.

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What this paper is about

This note generalizes previous results on the asymptotic equivalence of Ordinary and Generalized Least Squares estimates in Linear Regression models with trending data.

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OpenAlex reports 5 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

This note generalizes previous results on the asymptotic equivalence of Ordinary and Generalized Least Squares estimates in Linear Regression models with trending data.

Key concepts: Ordinary least squares, Autoregressive model, Mathematics, Equivalence (formal languages), Generalized least squares, Total least squares, Least-squares function approximation, Non-linear least squares

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Asymptotic Equivalence of Ordinary Least Squares and Generalized Least Squares with Trending Regressors and Stationary Autoregressive Disturbances — Research Paper | ScholarLens