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Mathematical Modeling

ISBN-10: 0123869129

ISBN-13: 9780123869128

Edition: 4th 2013

Authors: Mark Meerschaert

List price: $109.95
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Description:

Meerschaert's new edition strengthens his position as the survey text of choice for mathematical modeling courses, adding ample instructor support and leveraging on-line delivery for solutions manuals and software ancillaries. From genetic engineering to hurricane prediction, mathematical models guide much of the decision-making in our society, and if the assumptions and methods underlying the modeling are flawed, the outcome can be disastrously poor, as recent events have proved. Since mathematical modeling is a rapidly growing specialty with applications in so many scientific and technical disciplines, there is a need for mathematically rigorous treatments of the subject, and particularly for texts that expose students to a range of possible approaches. Offers increased support for instructors, including MATLAB material as well as other on-line resourcesFeatures new sections on time series analysis and diffusion modelsProvides additional problems with international focus such as whale and dolphin populations, plus updated optimization problems
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Book details

List price: $109.95
Edition: 4th
Copyright year: 2013
Publisher: Elsevier Science & Technology Books
Publication date: 3/7/2013
Binding: Hardcover
Pages: 384
Size: 6.50" wide x 9.50" long x 1.00" tall
Weight: 1.804
Language: English

Mark M. Meerschaert is Chairperson of the Department of Statistics and Probability at Michigan State University and an Adjunct Professor in the Department of Physics at the University of Nevada. Professor Meerschaert has professional experience in the areas of probability, statistics, statistical physics, mathematical modeling, operations research, partial differential equations, ground water and surface water hydrology. He started his professional career in 1979 as a systems analyst at Vector Research, Inc. of Ann Arbor and Washington D.C., where he worked on a wide variety of modeling projects for government and industry. Meerschaert earned his doctorate in Mathematics from the University of Michigan in 1984. He has taught at the University of Michigan, Albion College, Michigan State University, the University of Nevada in Reno, and the University of Otago in Dunedin, New Zealand. His current research interests include limit theorems and parameter estimation for infinite variance probability models, heavy tail models in finance, modeling river flows with heavy tails and periodic covariance structure, anomalous diffusion, continuous time random walks, fractional derivatives and fractional partial differential equations, and ground water flow and transport. For more details, see his personal web page http://www.stt.msu.edu/~mcubed

Optimization Models
One-Variable Optimization
Multivariable Optimization
Computational Methods for Optimization
Dynamic Models
Introduction to Dynamic Models
Analysis of Dynamic Models
Simulation of Dynamic Models
Probability Models
Introduction to Probability Models
Stochastic Models
Simulation of Probability Models