Nonparametric estimation of the mixing distribution in mixed models with random intercepts and slopes

Nonparametric estimation of the mixing distribution in mixed models with random intercepts and slopes

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Generalized linear mixture models (GLMM) are widely used in statistical applications to model count and binary data. We consider the problem of nonparametric likelihood estimation of mixing distributions in GLMM's with multiple random effects. The log-likelihood to be maximized has the general...

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Bibliographic Details
Main Author: Saab, Rabih
Other Authors: Lesperance, M. L.
Language:English
en
Published: 2013
Subjects:
Nonparametric maximum likelihood estimation
geometry of mixture likelihood
Poisson mixture model
Bernoulli mixture model
Direct Search
directional derivative
Zero-inflated data
goodness-of-fit
model selection
Online Access:http://hdl.handle.net/1828/4548

Internet

http://hdl.handle.net/1828/4548

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