Parameter estimation for discretely-observed linear
birth-and-death processes

J 2021

Parameter estimation for discretely-observed linear birth-and-death processes

DAVISON, Anthony, Sophie HAUTPHENNE a Andrea KRAUS

Základní údaje

Originální název

Parameter estimation for discretely-observed linear birth-and-death processes

Autoři

DAVISON, Anthony (826 Velká Británie a Severní Irsko), Sophie HAUTPHENNE (56 Belgie) a Andrea KRAUS (703 Slovensko, garant, domácí)

Vydání

Biometrics, Hoboken, Wiley, 2021, 0006-341X

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

10103 Statistics and probability

Stát vydavatele

Spojené státy

Utajení

není předmětem státního či obchodního tajemství

Odkazy

URL

Impakt faktor

Impact factor: 1.701

Kód RIV

RIV/00216224:14310/21:00118727

Organizační jednotka

Přírodovědecká fakulta

DOI

http://dx.doi.org/10.1111/biom.13282

UT WoS

000530927000001

Klíčová slova anglicky

Galton-Watson process; Gaussian approximation; likelihood; linear birth-and-death process; saddlepoint approximation

Štítky

rivok

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 29. 3. 2021 14:50, Mgr. Marie Šípková, DiS.

Anotace

V originále

Birth-and-death processes are widely used to model the development of biological populations. Although they are relatively simple models, their parameters can be challenging to estimate, as the likelihood can become numerically unstable when data arise from the most common sampling schemes, such as annual population censuses. A further difficulty arises when the discrete observations are not equi-spaced, for example, when census data are unavailable for some years. We present two approaches to estimating the birth, death, and growth rates of a discretely observed linear birth-and-death process: via an embedded Galton-Watson process and by maximizing a saddlepoint approximation to the likelihood. We study asymptotic properties of the estimators, compare them on numerical examples, and apply the methodology to data on monitored populations.

Návaznosti

GJ17-22950Y, projekt VaV

Název: Statistická inference pro složité náhodné procesy v ekonometrickém modelování

Investor: Grantová agentura ČR, Statistická inference pro složité náhodné procesy v ekonometrickém modelování

Citovat

DAVISON, Anthony, Sophie HAUTPHENNE a Andrea KRAUS. Parameter estimation for discretely-observed linear birth-and-death processes. Biometrics. Hoboken: Wiley, 2021, roč. 77, č. 1, s. 186-196. ISSN 0006-341X. Dostupné z: https://dx.doi.org/10.1111/biom.13282.

@article{1642516,
   author = {Davison, Anthony and Hautphenne, Sophie and Kraus, Andrea},
   article_location = {Hoboken},
   article_number = {1},
   doi = {http://dx.doi.org/10.1111/biom.13282},
   keywords = {Galton-Watson process; Gaussian approximation; likelihood; linear birth-and-death process; saddlepoint approximation},
   language = {eng},
   issn = {0006-341X},
   journal = {Biometrics},
   title = {Parameter estimation for discretely-observed linear birth-and-death processes},
   url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/biom.13282},
   volume = {77},
   year = {2021}
}

TY  - JOUR
ID  - 1642516
AU  - Davison, Anthony - Hautphenne, Sophie - Kraus, Andrea
PY  - 2021
TI  - Parameter estimation for discretely-observed linear birth-and-death processes
JF  - Biometrics
VL  - 77
IS  - 1
SP  - 186-196
EP  - 186-196
PB  - Wiley
SN  - 0006341X
KW  - Galton-Watson process
KW  - Gaussian approximation
KW  - likelihood
KW  - linear birth-and-death process
KW  - saddlepoint approximation
UR  - https://onlinelibrary.wiley.com/doi/abs/10.1111/biom.13282
L2  - https://onlinelibrary.wiley.com/doi/abs/10.1111/biom.13282
N2  - Birth-and-death processes are widely used to model the development of biological populations. Although they are relatively simple models, their parameters can be challenging to estimate, as the likelihood can become numerically unstable when data arise from the most common sampling schemes, such as annual population censuses. A further difficulty arises when the discrete observations are not equi-spaced, for example, when census data are unavailable for some years. We present two approaches to estimating the birth, death, and growth rates of a discretely observed linear birth-and-death process: via an embedded Galton-Watson process and by maximizing a saddlepoint approximation to the likelihood. We study asymptotic properties of the estimators, compare them on numerical examples, and apply the methodology to data on monitored populations.
ER  -

DAVISON, Anthony, Sophie HAUTPHENNE a Andrea KRAUS. Parameter estimation for discretely-observed linear birth-and-death processes. \textit{Biometrics}. Hoboken: Wiley, 2021, roč.~77, č.~1, s.~186-196. ISSN~0006-341X. Dostupné z: https://dx.doi.org/10.1111/biom.13282.

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