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October 2008 On the Behrens–Fisher problem: A globally convergent algorithm and a finite-sample study of the Wald, LR and LM tests
Alexandre Belloni, Gustavo Didier
Ann. Statist. 36(5): 2377-2408 (October 2008). DOI: 10.1214/07-AOS528

Abstract

In this paper we provide a provably convergent algorithm for the multivariate Gaussian Maximum Likelihood version of the Behrens–Fisher Problem. Our work builds upon a formulation of the log-likelihood function proposed by Buot and Richards [5]. Instead of focusing on the first order optimality conditions, the algorithm aims directly for the maximization of the log-likelihood function itself to achieve a global solution. Convergence proof and complexity estimates are provided for the algorithm. Computational experiments illustrate the applicability of such methods to high-dimensional data. We also discuss how to extend the proposed methodology to a broader class of problems.

We establish a systematic algebraic relation between the Wald, Likelihood Ratio and Lagrangian Multiplier Test (WLRLM) in the context of the Behrens–Fisher Problem. Moreover, we use our algorithm to computationally investigate the finite-sample size and power of the Wald, Likelihood Ratio and Lagrange Multiplier Tests, which previously were only available through asymptotic results. The methods developed here are applicable to much higher dimensional settings than the ones available in the literature. This allows us to better capture the role of high dimensionality on the actual size and power of the tests for finite samples.

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Alexandre Belloni. Gustavo Didier. "On the Behrens–Fisher problem: A globally convergent algorithm and a finite-sample study of the Wald, LR and LM tests." Ann. Statist. 36 (5) 2377 - 2408, October 2008. https://doi.org/10.1214/07-AOS528

Information

Published: October 2008
First available in Project Euclid: 13 October 2008

zbMATH: 1274.62379
MathSciNet: MR2458191
Digital Object Identifier: 10.1214/07-AOS528

Subjects:
Primary: 62H15

Keywords: algorithm , Behrens–Fisher Problem , High-dimensional data , Hypothesis testing , Lagrange multiplier test , likelihood ratio test , power , size , Wald test

Rights: Copyright © 2008 Institute of Mathematical Statistics

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Vol.36 • No. 5 • October 2008
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