Document Type

Journal Article

Department/Unit

Department of Mathematics

Language

English

Abstract

A maximum likelihood procedure is given for estimating parameters in a germination-growth process, based on germination times only or on both times and locations. The process is assumed to be driven by a Poisson process whose intensity is of known analytical form. The procedure is shown to perform well on simulated data with unnormalised gamma intensity and is also applied to data on release of neurotransmitter at a synapse.

Keywords

Germination-growth, Maximum Likelihood Estimation, Neurobiology, Poisson, Synapse

Publication Date

10-2003

Source Publication Title

Journal of Statistical Computation and Simulation

Volume

73

Issue

10

Start Page

725

End Page

732

Publisher

Taylor & Francis

Peer Reviewed

1

Copyright

This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of Statistical Computation and Simulation in October 2003, available online: http://www.tandfonline.com/10.1080/0094965031000078855.

Funder

SNC and ISM were supported by the UK/Hong Kong Joint Research Scheme, and by a Visiting Fellowship grant from the UK Engineering and Physical Sciences Research Council. SNC and MPQ were supported by the Research Grants Council of the Hong Kong Special Administrative Region, China (Project no. HKBU/2075/98P) and an FRG grant of the Hong Kong Baptist University.

DOI

10.1080/0094965031000078855

Link to Publisher's Edition

http://dx.doi.org/10.1080/0094965031000078855

ISSN (print)

00949655

ISSN (electronic)

15635163

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Mathematics Commons

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