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Non-Gaussian bifurcating models and quasi-likelihood estimation

Part of: Inference from stochastic processes Applications

Published online by Cambridge University Press:  14 July 2016

I. V. Basawa  and
J. Zhou
I. V. Basawa
Affiliation:
Department of Statistics, University of Georgia, 101 Cedar Street, Athens, GA 30602-1952, USA. Email address: ishwar@stat.uga.edu
J. Zhou
Affiliation:
Department of Statistics, University of Georgia, 101 Cedar Street, Athens, GA 30602-1952, USA. Email address: jinzhou@stat.uga.edu
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Abstract

A general class of Markovian non-Gaussian bifurcating models for cell lineage data is presented. Examples include bifurcating autoregression, random coefficient autoregression, bivariate exponential, bivariate gamma, and bivariate Poisson models. Quasi-likelihood estimation for the model parameters and large-sample properties of the estimates are discussed.

Keywords

Tree-indexed databifurcating autoregressive modelsmaximum likelihoodquasi-likelihood estimationMarkovian models

MSC classification

Primary: 62P10: Applications to biology and medical sciences
Secondary: 62M99: None of the above, but in this section
Type
Part 2. Estimation methods
Information
Journal of Applied Probability , Volume 41 , Issue A: Stochastic Methods and their Applications , 2004 , pp. 55 - 64
Copyright
Copyright © Applied Probability Trust 2004 

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