Maximum Likelihood Estimator and Likelihood Ratio Test in Complex Models: An Application to B Lymphocyte Development

Malka Gorfine*, Laurence Freedman, Gitit Shahaf, Ramit Mehr

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Pages (from-to)1131-1139
Number of pages9
JournalBulletin of Mathematical Biology
Volume65
Issue number6
DOIs
StatePublished - Nov 2003
Externally publishedYes

Funding

FundersFunder number
Dorot Science Fellowship Foundation759/01-1
Yigal Alon Fellowship
Bar-Ilan University
Israel Science Foundation

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