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A new vision on ordinary least squares estimation of parameters of linear model

K. Lakshmi, B. Mahaboob, D. Sateesh Kumar, Gyan Prakash, Tentu Nageswara Rao

2021AIP conference proceedings11 citationsDOIOpen Access PDF

Abstract

This paper aims at the method of OLS estimation of parameters of linear model. Here an innovative proof of Gauss-Markoff theorem for linear estimation has been presented.An extensive discussion in evaluating BLUE of a linear parametric function of the classical linear model is made by using the Gauss-Markoff theorem. Furthermore the importance of mean vector and variance-covariance matrix of BLUE are discussed. Moreover generalized Gauss-Markoff theorem for linear estimation, characteristic properties of OLS estimators and problems of linear statistical model by violating the assumptions are extensively discussed.

Topics & Concepts

Ordinary least squaresNon-linear least squaresGeneralized least squaresLeast-squares function approximationLinear modelIteratively reweighted least squaresComputer scienceArtificial intelligenceMathematicsApplied mathematicsEstimation theoryStatisticsAlgorithmEstimatorStatistical and numerical algorithmsRegional Economic and Spatial AnalysisControl Systems and Identification
A new vision on ordinary least squares estimation of parameters of linear model | Litcius