ArticleJournal of statistical planning and inference2011
Quasi- and pseudo-maximum likelihood estimators for discretely observed continuous-time Markov branching processes.
Article in Journal of statistical planning and inference, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Asymptotic behavior of cell populations described by two-type reducible age-dependent branching processes with non-homogeneous immigration().Mathematical population studies · 2012Article
- Quasi- and pseudo-maximum likelihood estimators for discretely observed continuous-time Markov branching processes.Journal of statistical planning and inference · 2011Article
- Two-Type Age-Dependent Branching Processes with Inhomogeneous Immigration as Models of Renewing Cell Populations.Pliska. Pliiska · 2011Article
- A composite likelihood approach to the analysis of longitudinal clonal data on multitype cellular systems under an age-dependent branching process.Biostatistics (Oxford, England) · 2011Article
- An age-dependent branching process model for the analysis of CFSE-labeling experiments.Biology direct · 2010Article
- Saddlepoint approximations to the moments of multitype age-dependent branching processes, with applications.Biometrics · 2010Article
- Stochastic modeling of oligodendrocyte generation in cell culture: model validation with time-lapse data.Theoretical biology & medical modelling · 2006Article
- A test of homogeneity for age-dependent branching processes with immigration.Electronic journal of statisticsArticle
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Authors and funding
2 authors.
Funding
Abstract
This article deals with quasi- and pseudo-likelihood estimation in a class of continuous-time multi-type Markov branching processes observed at discrete points in time. "Conventional" and conditional estimation are discussed for both approaches. We compare their properties and identify situations where they lead to asymptotically equivalent estimators. Both approaches possess robustness properties, and coincide with maximum likelihood estimation in some cases. Quasi-likelihood functions involving only linear combinations of the data may be unable to estimate all model parameters. Remedial measures exist, including the resort either to non-linear functions of the data or to conditioning the moments on appropriate sigma-algebras. The method of pseudo-likelihood may also resolve this issue. We investigate the properties of these approaches in three examples: the pure birth process, the linear birth-and-death process, and a two-type process that generalizes the previous two examples. Simulations studies are conducted to evaluate performance in finite samples.
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Registered trials
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