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Improved score tests for exponential family nonlinear models

Author

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  • Alexsandro B. Cavalcanti
  • Denise A. Botter
  • Lúcia P. Barroso
  • Manoel Santos-Neto
  • Gauss M. Cordeiro

Abstract

This paper focuses on the corrections to the score test statistic under the exponential family nonlinear model. We use Monte Carlo simulations to compare the corrected statistics and their uncorrected versions and to examine the impact of the number of nuisance parameters on their finite-sample behaviors for the normal nonlinear regression model. The numerical results have shown that the corrected score statistic performs better than the uncorrected version. Finally, we perform a statistical analysis with real data by using the approach proposed in the article.

Suggested Citation

  • Alexsandro B. Cavalcanti & Denise A. Botter & Lúcia P. Barroso & Manoel Santos-Neto & Gauss M. Cordeiro, 2021. "Improved score tests for exponential family nonlinear models," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 50(15), pages 3731-3745, July.
    • Handle: RePEc:taf:lstaxx:v:50:y:2021:i:15:p:3731-3745
    DOI: 10.1080/03610926.2019.1710202
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