M-procedures in the general multivariate nonlinear regression model

VICTOR ELISEO LEIVA SANCHEZ, Antonio Sanhueza, Pranab K. Sen, Nelson Araneda

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

In the multivariate nonlinear regression model, parameter estimators and test statistics based on least squares and maximum likelihood methods are usually nonrobust. For this type of models, we introduce M-estimators and M-tests, which are robust to departures from normality. In addition, we study the asymptotic properties and consider a computational algorithm for these estimators.

Original languageEnglish
Pages (from-to)1-13
Number of pages13
JournalPakistan Journal of Statistics
Volume26
Issue number1
StatePublished - 1 Jan 2010

Keywords

  • Asymptotic normality
  • Efficiency
  • M-estimators
  • M-tests
  • Uniform asymptotic linearity

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