Written in English
|Statement||by Ernesto Lorda.|
|The Physical Object|
|Pagination||x, 182 leaves|
|Number of Pages||182|
Infinite Leslie matrices are studied. The purely linear algebraic concept of weighed kneading determinant is introduced to solve linear difference equations associated with Leslie matrices. The dynamics of a delayed stochastic model simulating wastewater treatment process are studied. Leslie matrices arise in a mathematical model for population growth and the eigenvalues of a Leslie matrix are important in describing the limiting behaviour of the corresponding population model. In this paper, a stochastic predator–prey model with modified Leslie–Gower Holling-type II schemes and impulsive toxicant input in polluted environments is developed and analyzed. The threshold between persistence in the mean and extinction is established for each clic-clelia.com by:
One of the impor- tant properties in population dynamics is the persistence which means every species will never become extinct. The most natural analogue for the stochastic population dynamics () is that every species will never become extinct with probability 1. Cited by: nonlinear and stochastic dynamics, and the methods used, geared toward graduate students in physics, mathematics, and engineering and the researchers who are interested in . The biological system is complex to model, partly because a stock of fish interacts richly with other fish stocks as predators or prey, and with the changing currents, temperatures and other aspects of the marine environment. The biological system is also difficult to model because so little about it is known. Introduction to Stochastic Population Models Thomas E. Wehrly Department of Statistics Texas A&M University June 13,
Snake populations are generally decreasing due to habitat loss, loss of prey, and killing by humans. For specific species in the USA, check with your state fish and wildlife agency, or with the US Fish and Wildlife Service. Countries other than the US often have conservation programs, research studies. This chapter deals with stochastic models for structured populations whose dynamics depend crucially on individual characteristics such as age, size, or location. We deal with linear stochastic models, and their analysis is also essential to the analysis of nonlinear stochastic models, particularly their boundary behavior which determines Cited by: 1. 1. Stochastic Modeling 5. ities used in odds making are often called subjective probabilities. Then, odds making forms the third principle for assigning probability values in models . In this study, population dynamics is described using a stochastic model, where population is put into distinct and disjoint age classes: Juvenile, sub-Adult, Adult, Resting-Adult Author: Kirui Wesley, Rotich Titus.