Bulletin of Mathematical Biology

, Volume 65, Issue 6, pp 1131–1139

Maximum likelihood estimator and likelihood ratio test in complex models: An application to B lymphocyte development

  • Malka Gorfine
  • Laurence Freedman
  • Gitit Shahaf
  • Ramit Mehr
Article

DOI: 10.1016/S0092-8240(03)00062-4

Cite this article as:
Gorfine, M., Freedman, L., Shahaf, G. et al. Bull. Math. Biol. (2003) 65: 1131. doi:10.1016/S0092-8240(03)00062-4

Abstract

In this paper we introduce a simple framework which provides a basis for estimating parameters and testing statistical hypotheses in complex models. The only assumption that is made in the model describing the process under study, is that the deviations of the observations from the model have a multivariate normal distribution. The application of the statistical techniques presented in this paper may have considerable utility in the analysis of a wide variety of complex biological and epidemiological models. To our knowledge, the model and methods described here have not previously been published in the area of theoretical immunology.

Copyright information

© Society for Mathematical Biology 2003

Authors and Affiliations

  • Malka Gorfine
    • 1
  • Laurence Freedman
    • 1
  • Gitit Shahaf
    • 2
  • Ramit Mehr
    • 2
  1. 1.Department of Mathematics and StatisticsBar-Ilan UniversityRamat-GanIsrael
  2. 2.Faculty of Life SciencesBar-Ilan UniversityRamat-GanIsrael