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

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14310%2F21%3A00118727" target="_blank" >RIV/00216224:14310/21:00118727 - isvavai.cz</a>

Výsledek na webu

<a href="https://onlinelibrary.wiley.com/doi/abs/10.1111/biom.13282" target="_blank" >https://onlinelibrary.wiley.com/doi/abs/10.1111/biom.13282</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1111/biom.13282" target="_blank" >10.1111/biom.13282</a>

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

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

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10103 - Statistics and probability

Projekt

<a href="/cs/project/GJ17-22950Y" target="_blank" >GJ17-22950Y: Statistická inference pro složité náhodné procesy v ekonometrickém modelování</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2021

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Biometrics

ISSN

0006-341X

e-ISSN

1541-0420

Svazek periodika

77

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

11

Strana od-do

186-196

Kód UT WoS článku

000530927000001

EID výsledku v databázi Scopus

2-s2.0-85085068936