Mathematical Methods of Population Biology

Hoppensteadt, Frank C.

ISBN 10: 052128256X / ISBN 13: 9780521282567

Edité par Cambridge University Press, Cambridge UK, 1982

A propos de cet article

In the Cambridge Studies in Mathematical Biology series. "Exercises,for which solutions are provided, illustrate material in the text and also deal with models more advanced than those derived and studied in the text." 149 pages; 5 1/2 x 8 1/2 ".

N° de réf. du vendeur 44643

Détails bibliographiques

• Titre: Mathematical Methods of Population Biology
• Éditeur: Cambridge University Press, Cambridge UK
• Date de parution: 1982
• Langue: anglais
• ISBN à 10 chiffres: 052128256X
• ISBN à 13 chiffres: 9780521282567
• Reliure: Paperback
• État de l'article: Near Fine
• Catalogues du vendeur:
  • Nature

A propos de ce titre

Synopsis

This introduction to mathematical methods that are useful for studying population phenomena is intended for advanced undergraduate and graduate students, and will be accessible to scientists who do not have a strong mathematics background.

Présentation de l'éditeur

This introduction to mathematical methods that are useful for studying population phenomena is intended for advanced undergraduate and graduate students, and will be accessible to scientists who do not have a strong mathematics background. The material is graded in mathematical difficulty. The earlier parts of the book involve elementary diference equations while later chapters present topics that require more mathematical preparation. Models of total population and population age structure are first derived and studied, and then models of random population events are presented in terms of Markov chains. The last two chapters deal with mathematical methods used to uncover qualitative behaviour of more complicated difference equations. Each chapter begins with a simple model, usually of some historical interest, that defines the primary goals of the chapter. Exercises, for which solutions are provided, illustrate material in the text and also deal with models more advanced than those derived and studied in the text.