Means of Equilibrium Analysis in the Dieckmann–Law Population Dynamics Model

The authors study the main approaches to studying the stochastic process of population dynamics of immovable individuals with continuous time and space. A procedure for closing spatial moments is described along with ways of solving the resulting system of integro-differential equations corresponding to the dynamics of the process’s spatial moments. The spatial moments obtained in different ways and closures are confirmed by comparing them to spatial statistics for modeling a stochastic space-time point process of birth–scatter–death in a limited area with periodic boundary conditions.

Authors

Institutions

Publication Details

Journal
Moscow University Computational Mathematics and Cybernetics
Published
2024-12-01
DOI
https://doi.org/10.3103/s0278641924700195
Primary Topic
Innovation Diffusion and Forecasting
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Means of Equilibrium Analysis in the Dieckmann–Law Population Dynamics Model

M. V. Nikolaev, A. A. Nikitin, E. G. Galkin, L. V. Inozemtsev
Moscow University Computational Mathematics and Cybernetics
Innovation Diffusion and Forecasting
article

Means of Equilibrium Analysis in the Dieckmann–Law Population Dynamics Model

M. V. Nikolaev, A. A. Nikitin, E. G. Galkin, L. V. Inozemtsev
article en

Abstract

The authors study the main approaches to studying the stochastic process of population dynamics of immovable individuals with continuous time and space. A procedure for closing spatial moments is described along with ways of solving the resulting system of integro-differential equations corresponding to the dynamics of the process’s spatial moments. The spatial moments obtained in different ways and closures are confirmed by comparing them to spatial statistics for modeling a stochastic space-time point process of birth–scatter–death in a limited area with periodic boundary conditions.

Moscow University Computational Mathematics and CyberneticsVol. 48(4)
Lomonosov Moscow State University (RU), Swansea University (GB), Vrije Universiteit Amsterdam (NL)
Openalex Percentile: Top 66%
Innovation Diffusion and Forecasting
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.