Median bias reduction of maximum likelihood estimates

E C Kenne Pagui, A Salvan and N Sartori

Biometrika, 2017, vol. 104, issue 4, 923-938

Abstract: For regular parametric problems, we show how median centring of the maximum likelihood estimate can be achieved by a simple modification of the score equation. For a scalar parameter of interest, the estimator is equivariant under interest-respecting reparameterizations and is third-order median unbiased. With a vector parameter of interest, componentwise equivariance and third-order median centring are obtained. Like the implicit method of Firth (1993) for bias reduction, the new method does not require finiteness of the maximum likelihood estimate and is effective in preventing infinite estimates. Simulation results for continuous and discrete models, including binary and beta regression, confirm that the method succeeds in achieving componentwise median centring and in solving the boundary estimate problem, while keeping comparable dispersion and the same approximate distribution as its main competitors.

Keywords: Beta regression; Binary regression; Boundary estimate; Modified score; Parameterization invariance; Tensor (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (3)

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