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The “Maximum Likelihood Solution” of the Problem of Estimating a Linear Functional Relationship
87
Citations
3
References
1969
Year
Functional RelationshipParameter EstimationDensity EstimationEngineeringUnsatisfactory Maximum-likelihood EstimatorsRobust StatisticUncertainty QuantificationEstimation StatisticLikelihood ApproachStatistical InferenceEstimation TheoryFunctional Data AnalysisStatisticsLinear Functional RelationshipSemi-nonparametric Estimation
Summary The problem considered is that of estimating a functional relationship (assumed linear) between two unobservable mathematical quantities ξ and η from pairs of observations on these quantities when both sets of observations are subject to normal independent errors. The problem has attracted much interest over a long period and one reads repeatedly that the method of maximum likelihood yields unsatisfactory estimators in this case. In this note we show that in fact no maximum-likelihood solution exists for this problem, which ceases then to provide an example of unsatisfactory maximum-likelihood estimators and merely joins the queue of problems in which the likelihood approach fails to produce estimators. The distinction, although academic, is worth making.
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