Maximum likelihood estimation for germination-growth processes with application to neurotransmitters data

S. N. Chiu; I. S. Molchanov; M. P. Quine

doi:10.1080/0094965031000078855

Maximum likelihood estimation for germination-growth processes with application to neurotransmitters data

S. N. Chiu^*, I. S. Molchanov, M. P. Quine

^*Corresponding author for this work

Department of Mathematics

Research output: Contribution to journal › Journal article › peer-review

6 Citations (Scopus)

26 Downloads (Pure)

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.

Original language	English
Pages (from-to)	725-732
Number of pages	8
Journal	Journal of Statistical Computation and Simulation
Volume	73
Issue number	10
DOIs	https://doi.org/10.1080/0094965031000078855
Publication status	Published - 1 Oct 2003

Scopus Subject Areas

Statistics and Probability
Modelling and Simulation
Statistics, Probability and Uncertainty
Applied Mathematics

User-Defined Keywords

Germination-growth
Maximum likelihood estimation
Neurobiology
Poisson
Synapse

Access to Document

10.1080/0094965031000078855

Full TextAccepted author manuscript, 117 KB

Cite this

@article{a4a5550c9b80457ba9364ea7a12c4179,

title = "Maximum likelihood estimation for germination-growth processes with application to neurotransmitters data",

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",

author = "Chiu, {S. N.} and Molchanov, {I. S.} and Quine, {M. P.}",

note = "Funding Information: 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.",

year = "2003",

month = oct,

day = "1",

doi = "10.1080/0094965031000078855",

language = "English",

volume = "73",

pages = "725--732",

journal = "Journal of Statistical Computation and Simulation",

issn = "0094-9655",

publisher = "Taylor and Francis",

number = "10",

}

TY - JOUR

T1 - Maximum likelihood estimation for germination-growth processes with application to neurotransmitters data

AU - Chiu, S. N.

AU - Molchanov, I. S.

AU - Quine, M. P.

N1 - Funding Information: 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.

PY - 2003/10/1

Y1 - 2003/10/1

N2 - 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.

AB - 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.

KW - Germination-growth

KW - Maximum likelihood estimation

KW - Neurobiology

KW - Poisson

KW - Synapse

UR - http://www.scopus.com/inward/record.url?scp=0142136674&partnerID=8YFLogxK

U2 - 10.1080/0094965031000078855

DO - 10.1080/0094965031000078855

M3 - Journal article

AN - SCOPUS:0142136674

SN - 0094-9655

VL - 73

SP - 725

EP - 732

JO - Journal of Statistical Computation and Simulation

JF - Journal of Statistical Computation and Simulation

IS - 10

ER -

Maximum likelihood estimation for germination-growth processes with application to neurotransmitters data

Abstract

Scopus Subject Areas

User-Defined Keywords

Access to Document

Other files and links

Fingerprint

Cite this