Parameter estimation for multivariate population processes: a saddlepoint approach-Reference-Cited by-同舟云学术

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Parameter estimation for multivariate population processes: a saddlepoint approach

Published:2020-10-22 Issue:1 Volume:37 Page:168-196
ISSN:1532-6349
Container-title:Stochastic Models
language:en
Short-container-title:Stochastic Models

Author:

de Gunst Mathisca¹,Hautphenne Sophie²,Mandjes Michel³,Sollie Birgit¹

Affiliation:

1. Mathematics, VU University Amsterdam, Amsterdam, Netherlands

2. School of Mathematics and Statistics, The University of Melbourne, Parkville, Victoria Melbourne, Australia

3. University of Amsterdam Korteweg-de Vries Institute for Mathematics, Amsterdam, Netherlands

Funder

NWO Gravitation project Networks

Publisher

Informa UK Limited

Subject

Applied Mathematics,Modeling and Simulation,Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/15326349.2020.1832895

Reference23 articles.

1. Quasi- and pseudo-maximum likelihood estimators for discretely observed continuous-time Markov branching processes

2. Estimation for General Birth-Death Processes

3. Davison, A.; Hautphenne, S.; Kraus, A. 2018. Parameter estimation for discretely observed linear birth-and-death processes. arXiv: 1802.05015.

4. The linear birth‒death process: an inferential retrospective

5. Likelihood-based inference for discretely observed birth-death-shift processes, with applications to evolution of mobile genetic elements

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2. A Numerical Approach for Evaluating the Time-Dependent Distribution of a Quasi Birth-Death Process;Methodology and Computing in Applied Probability;2021-07-15

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