Robust inference for nonlinear regression models

Ana M. Bianco () and Paula M. Spano ()
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Ana M. Bianco: Universidad de Buenos Aires and CONICET, Ciudad Universitaria
Paula M. Spano: Universidad de Buenos Aires and CONICET, Ciudad Universitaria

TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, 2019, vol. 28, issue 2, No 12, 369-398

Abstract: Abstract A family of weighted estimators of the regression parameter under a nonlinear model is introduced. The proposed weighted estimators are computed through a four-step MM-procedure, and the given approach allows for possible missing responses. Under mild conditions, the proposed estimators turn to be consistent and asymptotically normal. A robust Wald-type test statistic based on this family of estimators is also provided, and its asymptotic distribution is derived under the null and contiguous hypotheses. The local robustness of the proposed procedures is studied via the influence function analysis, and the finite sample behaviour of the estimators and tests is investigated through a Monte Carlo study in different contaminated scenarios. An application to an environmental data set illustrates the procedure.

Keywords: Nonlinear regression; MM-procedure; Robust estimation; Robust hypothesis testing; Missing at random; MSC 62F35; MSC 62F10; MSC 62F03 (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s11749-017-0570-2

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