Mathematical modelling

Practical introduction for advanced undergraduate or beginning graduate students of applied mathematics, developed at the University of Oxford.

With examples drawn from contemporary physics this book clearly explains the mathematics graduate students need to succeed in their courses.

Employs basic mathematical skills to teach students how to address topical, real-world problems using quantitative reasoning.

Employs basic mathematical skills to teach students how to address topical, real-world problems using quantitative reasoning.

The theory, methods and applications of matrix analysis are presented here in a novel theoretical framework.

The theory, methods and applications of matrix analysis are presented here in a novel theoretical framework.

A guide to solving numerical problems in the biological sciences, with extensive worked examples and exercises of varying difficulty.

Connecting theory with clinical applications, this book uses mathematical models to explain and study organ biomechanics of the abdominal viscera.

The Dynamic Energy Budget theory unifies the commonalities between organisms and links different levels of biological organisation.

A theoretical treatment of nonlinear behaviour of solids and structures, suitable for numerical computation.

Presents numerical methods and computer code in Matlab for the solution of ODEs and PDEs with detailed line-by-line discussion.

Emphasises the power of mathematics to provide quantitative insights across the whole area of solid mechanics; accessible and comprehensive.

Textbook for graduate students and an introduction for researchers to coastal basins through simple hydrodynamics.

A concise, systematic introduction to the principles of analysis of variance for post-graduates and professionals.

Treats Model I ANOVA and linear regression models with non-random predictors in a finite-dimensional setting.

A friendly 2007 guide to mathematical modelling for evolutionary and behavioural ecologists.

This 2007 book discusses the design of reliable numerical methods to retrieve missing information in models of complex systems.

Graduate text explaining how methods of nonlinear analysis can be used to tackle nonlinear differential equations.

This book applies techniques from quantum mechanics and quantum field theory to financial physics.

The authors describe the modelling of financial derivative products from an applied mathematician''s viewpoint.

This textbook provides a no-nonsense introduction to the principles of theoretical and mathematical biology.

This book, first published in 2006, examines the theory and practice of weather and climate predictability for graduate students and researchers.

Topics include: viscous flow, magnetohydrodynamics, atmospheric flows, shock equations, turbulence, nonlinear solid mechanics and solitons.

Linear and non-linear models of populations, molecular evolution, phylogenetic tree construction, genetics, and infectious diseases are presented with minimal prerequisites.

This 2002 book is an introduction to spiking neurons for advanced undergraduate or graduate students.

Presents a brief description of several ways in which mathematics and statistics are being used in genome analysis and sequencing.

A story of using computer simulations and mathematical modeling techniques to predict the outcome of jai-alai matches and bet on them successfully.

Beginning Algorithms A good understanding of algorithms, and the knowledge of when to apply them, is crucial to producing software that not only works correctly, but also performs efficiently.

A groundbreaking text and professional resource on natural attenuation technology Natural attenuation is rapidly becoming a widely used approach to manage groundwater and soil contamination by hazardous substances in petroleum-product releases and leachate from hazardous waste sites and landfills.

A thorough review of the most current regression methods in time series analysis Regression methods have been an integral part of time series analysis for over a century.

A significantly revised and improved introduction to a critical aspect of scientific computation Matrix computations lie at the heart of most scientific computational tasks.

The only guide to managing and integrating the open source model With the phenomenal success of Linux, companies are taking open source business solutions much more seriously than ever before.

The decision to implement environmental protection options is a political one.

The decision to implement environmental protection options is a political one.

At present there is no unified treatment, drawing together models to allow a consistent and reliable set of migration flows, across countries.

A guide to the validation and risk management of quantitative models used for pricing and hedging Whereas the majority of quantitative finance books focus on mathematics and risk management books focus on regulatory aspects, this book addresses the elements missed by this literature--the risks of the models themselves.

Groundwater is a vital source of water throughout the world.

Many ecological phenomena may be modelled using apparently random processes involving space (and possibly time).

Visual attention is a relatively new area of study combining a number of disciplines: artificial neural networks, artificial intelligence, vision science and psychology.

Ecologists and environmental managers rely on mathematical models, both to understand ecological systems and to predict future system behavior.

Spatial point processes are mathematical models used to describe and analyse the geometrical structure of patterns formed by objects that are irregularly or randomly distributed in one-, two- or three-dimensional space.

Complex mathematical and computational models are used in all areas of society and technology and yet model based science is increasingly contested or refuted, especially when models are applied to controversial themes in domains such as health, the environment or the economy.

An insightful presentation of the key concepts, paradigms, and applications of modeling and simulation Modeling and simulation has become an integral part of research and development across many fields of study, having evolved from a tool to a discipline in less than two decades.

An accessible guide to developing intuition and skills for solving mathematical problems in the physical sciences and engineering Equations play a central role in problem solving across various fields of study.

one-of-a-kind introduction to the theory and application of modeling and simulation techniques in the realm of international studies Modeling and Simulation for Analyzing Global Events provides an orientation to the theory and application of modeling and simulation techniques in social science disciplines.

Explores wide-ranging applications of modeling and simulation techniques that allow readers to conduct research and ask "e;What if?

Praise for Modeling for Insight "e;Most books on modeling are either too theoretical or too focused on the mechanics of programming.

Beginning Algorithms A good understanding of algorithms, and the knowledge of when to apply them, is crucial to producing software that not only works correctly, but also performs efficiently.

A comprehensive, step-by-step introduction to wavelets in statistics.

A unique, integrated treatment of computer modeling and simulation "e;The future of science belongs to those willing to make the shift to simulation-based modeling,"e; predicts Rice Professor James Thompson, a leading modeler and computational statistician widely known for his original ideas and engaging style.