## Textbooks

SIAM publishes many graduate and undergraduate textbooks and books that can be used as supplemental course texts. Examples and problem sets are included in our textbooks, and solutions are often available in the book or as an online supplement. Many of our texts feature online components like additional problem sets, appendices, and program files.

If you are interested in considering one of our books for a course, please complete the Examination Copy Request Form.

If you have **already adopted** a SIAM text for classroom
use and need a copy of the text, please fill out our Desk
Copy Request Form. You will be asked to either a) provide us with
a link to your online syllabus showing the text as a required text, b)
fax us a copy of your syllabus showing the text as a required text, or
c) fax us a copy of your bookstore’s order confirmation for the
adopted text.

Textbooks are available in the following subject areas:

## Applied Geometry and Geometric Design

Approximation and Modeling with B-Splines

**Klaus Höllig and Jörg Hörner**

Appropriate as an advanced undergraduate or first-year graduate text for courses on splines or approximation and geometric modeling for students in mathematics, engineering, and computer science. Practitioners in these fields who are using B-splines in numerical simulations, computer-aided design, and visualization will also find the book useful in their work.

Introduction to the Mathematics of Subdivision Surfaces

Lars-Erik Andersson and Neil F. Stewart

Recommended for advanced graduate students. ** **

## Asymptotic and Perturbation Methods

Perturbations: Theory and Methods

**James A. Murdock**

Singular Perturbations and Hysteresis

**Michael P. Mortell, Robert E. O'Malley, Alexei Pokrovskii, and Vladimir Sobolev, Editors**

Asymptotic Approximations of Integrals

**R. Wong**

## Atmospheric and Oceanographic Sciences

Mathematics and Climate

**Hans Kaper and Hans Engler**

This book is written at the level of advanced undergraduate and beginning graduate students and assumes only basic familiarity with linear algebra, calculus, elementary differential equations, and statistics.

Spectral Numerical Weather Prediction Models

**Martin Ehrendorfer**

Intended as a primary text for advanced undergraduate/first year graduate.

## Biological Sciences

A Course in Mathematical Biology: Quantitative Modeling with Mathematical & Computational Methods

**Gerda de Vries, Thomas Hillen, Mark Lewis, Johannes Müller, and Birgitt Schönfisch**

Intended for upper level undergraduate students in mathematics or similar quantitative sciences. Also appropriate for beginning graduate students in biology, medicine, ecology, and other sciences.

--Sample Chapter

Mathematical Models in Biology

**Leah Edelstein-Keshet**

Recommended for undergraduate mathematical biology students.

A Primer on Mathematical Models in Biology**Lee A. Segel and Leah Edelstein-Keshet**

This book is intended for upper level undergraduates in mathematics, graduate students in biology, and lower-level graduate students in mathematics who would like exposure to biological applications.

Probabilistic Boolean Networks: The Modeling and Control of Gene Regulatory Networks**
Ilya Shmulevich and Edward R. Dougherty
**Recommended for all students.

## Computational Mathematics and Computer Science

Numerical Methods for Evolutionary Differential Equations

**Uri M. Ascher
**Recommended for graduate students.

A First Course in Numerical Methods

**Uri M. Ascher and Chen Greif**

Recommended as a primary text for undergraduate or first-year graduate students.

Computer Methods for Ordinary Differential Equations and Differential-Algebraic Equations

**Uri M. Ascher and Linda R. Petzold**

Recommended for senior undergraduate or beginning graduate students

Recipes for Continuation

**Harry Dankowicz and Frank Schilder**

This book is intended for students and teachers of nonlinear dynamics and engineering, as well as engineers and scientists engaged in modeling and simulation, and is valuable to potential developers of computational tools for analysis of nonlinear dynamical systems. It assumes some familiarity with MATLAB programming and a theoretical sophistication expected of upper-level undergraduate or first-year graduate students in applied mathematics and/or computational science and engineering.

Computational Matrix Analysis

**Alan J. Laub**

Intended for senior undergraduate and beginning graduate students.

Understanding
Search Engines: Mathematical Modeling and Text Retrieval, Second Edition

**Michael W. Berry and Murray Browne**

Recommended for all students.

Computational Methods for Multiphase Flows in Porous Media

**Zhangxin Chen, Guanren Huan, and Yuanle Ma**

Recommended for graduate or advanced undergraduate students.

--Sample Chapter

Numerical Linear Algebra and Applications, Second Edition

Biswa Nath Datta

Recommended for all students.

Learning MATLAB

**Tobin A. Driscoll **

Recommended for all students.

Numerical Methods for Special Functions

**Amparo Gil, Javier Segura, Nico Temme
**Recommended for general numerical analysis courses.

--Sample Chapter

MATLAB
Guide, Second Edition

**Desmond J. Higham and Nicholas J. Higham**

Recommended for all students.

Sample Chapter

Finite Element Methods with B-Splines

**Klaus Höllig**

Recommended for graduate students.

Numerical Matrix Analysis: Linear Systems and Least Squares

**Ilse C. F. Ipsen
**Recommended for advanced undergraduate and first year graduate students.

Solving
Nonlinear Equations with Newton's Method

**C. T. Kelley**

Recommended for graduate students with a working knowledge of MATLAB.

Parallel MATLAB for Multicore and Multinode Computers**
Jeremy Kepner
**Recommended for advanced undergraduate and graduate students.

Numerical
Computing with MATLAB

**Cleve Moler**

Recommended for all students.

Introduction to Interval Analysis

**Ramon E. Moore, R. Baker Kearfott, and Michael J. Cloud**

Recommended for all students.

Linear and Nonlinear Inverse Problems with practical Applications

**Jennifer Mueller and Samuli Siltanen**

Recommended for advanced undergraduate and graduate students.

Scientific Computing with Case Studies

**Dianne P. O'Leary **

Recommended for advanced undergraduate and graduate students.

Solving PDEs in C++: Numerical Methods in a Unified Object-Oriented Approach, Second Edition

**Yair Shapira**

Recommended for advanced undergraduate and graduate students.

Numerical Polynomial Algebra

**Hans J. Stetter**

Recommended for graduate students.

Spectral Methods in MATLAB

**Lloyd N. Trefethen**

Recommended for advanced undergraduate and graduate students studying numerical
methods for PDEs.

Insight Through Computing: A MATLAB Introduction to Computational Science and Engineering

Charles F. Van Loan and K.-Y. Daisy Fan

Recommended for undergraduate students.

The Matrix Eigenvalue Problem: GR and Krylov Subspace Methods

**David S. Watkins**

Intended for graduate students in numerical linear algebra

--Sample Chapter

## Control and Systems Theory

Approximation
of Large-Scale Dynamical Systems

**Athanasios C. Antoulas**

Recommended for graduate students.

--Sample
Chapter

Dynamic Noncooperative Game Theory, Second Edition

**Tamer Basar and Geert Jan Olsder**

Recommended for graduate-level courses on optimal control theory.

Practical Methods for Optimal Control and Estimation Using Nonlinear Programming, Second Editon

John T. Betts

Recommended for advanced undergraduate and graduate students.

Control Perspectives on Numerical Algorithms and Matrix Problems

**Amit Bhaya and Eugenius Kaszkurewicz**

Recommended for senior undergraduate and graduate students.

--Sample
Chapter

Shapes and Geometries: Metrics, Analysis, Differential Calculus, and Optimization, Second Edition

**M. C. Delfour and J.-P. Zolésio**

This book is intended for applied mathematicians and advanced engineers and scientists, but the book is also structured as an initiation to shape analysis and calculus techniques for a broader audience of mathematicians.

--Sample Chapter

Applied Stochastic
Processes and Control for Jump Diffusions: Modeling, Analysis, and
Computation

**Floyd B. Hanson**

This book is written for graduate students in applied mathematics, science and engineering.

--Sample Chapter

Classical
Control Using H∞ Methods: An Introduction to Design

**J. William Helton and Orlando Merino**

Recommended as supplementary text for students of control at any level; main
text for course on practial H∞ design.

Classical
Control Using H∞ Methods: Theory, Optimization, and Design

**J. William Helton and Orlando Merino**

Recommended for an advanced seminar in control theory in engineering departments
or applied functional or complex analysis in mathematics departments; second
course in control at senior undergraduate or beginning graduate level.

L1 Adaptive Control Theory: Guaranteed Robustness with Fast Adaptation

**Naira Hovakimyan and Chengyu Cao**

This book is intended for graduate students interested in pursuing new directions in research and developing technology at reduced costs.

Nonlinear
Output Regulation: Theory and Applications

**Jie Huang**

Recommended for graduate students.

Adaptive Control Tutorial

**Petros Ioannou and Baris Fidan **

Recommended for graduate students.

-- Sample Chapter

Singular Perturbation Methods in Control: Analysis and Design

**Petar Kokotovic, Hassan K. Khalil, and John O'Reilly**

Suitable for a graduate level introduction to singular perturbation methods in control.

Boundary Controls of PDEs: A Course on Backstepping Designs

**Miroslav Krstic and Andrey Smyshlyaev **

Recommended for graduate students.

Neuro-Fuzzy
Control of Industrial Systems with Actuator Nonlinearities

**F. L. Lewis, J. Campos, and R. Selmic**

Recommended for graduate students.

Stochastic Processes, Estimation, and Control

**Jason L. Speyer and Walter H. Chung**

Recommended for first year graduate students in systems and control.

Nonlinear
Systems Analysis, Second Edition

**M. Vidyasagar**

Recommended for graduate students.

Linear Feedback Control: Analysis and Design with MATLAB

**Dingyü Xue, YangQuan Chen, and Derek P. Atherton **

-- Sample Chapter

From Vector Spaces to Function Spaces: Introduction to Functional Analysis with Applications

**Y. Yamamoto**

Recommended for advanced undergraduate or graduate students.

## Data Mining

Graph Algorithms in the Language of Linear Algebra

**Jeremy Kepner and John Gilbert**

This book is suitable as the primary text for a class on linear algebraic graph algorithms and as either the primary or supplemental text for a class on graph algorithms for engineers and scientists without training in computer science.

Matrix Methods in Data Mining and Pattern Recognition

**Lars Eldén **

Suitable for undergraduate students who have previously taken an introductory scientific computing/numerical analysis course. Graduate students in various data mining and pattern recognition areas who need an introduction to linear algebra techniques will also find the book useful.

-- Sample Chapter

Scientific Data Mining: A Practical Perspective

**Chandrika Kamath
**Recommended for undergraduate and first-year graduate students.

## Dynamical Systems

Approximation
of Large-Scale Dynamical Systems

**Athanasios C. Antoulas**

Recommended for graduate students.

--Sample
Chapter

Simulating, Analyzing, and Animating Dynamical Systems: A Guide to XPPAUT for Researchers and Students

**Bard Ermentrout**

Hidden Markov Models and Dynamical Systems

**Andrew M. Fraser**

Recommended for advanced undergraduate and graduate students.

Numerical Methods for Bifurctaions of Dynamical Equilibria

**Willy J. F. Govaerts**

Recommended for graduate students.

Differential Dynamical Systems

**James D. Meiss**

Recommended for senior undergraduates and first-year graduate students.

-- Sample Chapter

## Economics

Mathematical Optimization and Economic Theory

**Michael D. Intriligator**

Recommended for graduate students and advanced undergraduate students.

Elementary Calculus of Financial Mathematics

**A. J. Roberts**

Recommended for undergraduate students.

## Education

Ants, Bikes, and Clocks: Problem Solving for Undergraduates

**William Briggs**

Handbook of Writing for the Mathematical Sciences, Second Edition

**Nicholas J. Higham**

## Fluid Mechanics

Transonic Aerodynamics: Problems in Asymptotic Theory

**L. Pamela Cook, Editor**

Vortex Methods and Vortex Motion

**Karl E. Gustafson and James A. Sethian, Editors**

Introduction to the Numerical Analysis of Incompressible Viscous Flows

**William Layton **

Recommended for graduate students.

Mathematical Biofluiddynamics

**Sir James Lighthill**

Mathematical Analysis of Viscoelastic Flows

**Michael Renardy**

Navier-Stokes Equations and Nonlinear Functional Analysis, Second Edition

**Roger Temam**

## Functional Analysis

Linear and Nonlinear Functional Analysis with Applications

Philippe G. Ciarlet

This book is intended for advanced undergraduates, graduate students, and researchers and is ideal for teaching or self-study.

## General Interest/Social Sciences

Mathematics of Social Choice: Voting, Compensation, and Division

Christoph Börgers

Recommended for
undergraduate students.

## Image Processing

Image Processing and Analysis: Variational, PDE, Wavelet, and Stochastic Methods

**Tony F. Chan and Jianhong (Jackie) Shen**

Recommended for graduate students.

Introduction to the Mathematics of Medical Imaging, Second Edition

**Charles L. Epstein**

Recommended for advanced undergraduate or beginning graduate level students.

--Sample Chapter

Deblurring Images: Matrices, Spectra, and Filtering

**Per Christian Hansen, James G. Nagy, and Dianne P. O’Leary**

Recommended for beginners in the field of image restoration and regularization.

--Sample Chapter

FAIR: Flexible Algorithms for Image Registration

Jan Modersitzki

Recommended for advanced graduate students.

## Linear Algebra and Matrix Theory

Analytic Perturbation Theory and Its Applications**Konstantin E. Avrachenkov, Jerzy A. Filar, and Phil G. Howlett**

Recommended for applied and pure mathematicians, researchers, and engineers interested in systems and control. It is also suitable for advanced undergraduate, first-year graduate, and advanced graduate one-semester classes covering perturbation theory in various mathematical uses.

Spectral Properties of Banded Toeplitz Matrices

**Albrecht Böttcher, Sergei M. Grudsky, Editors**

Portions of this text are suitable for use as a graduate-level text on Toeplitz matrices or analysis.

-- Sample
Chapter

Direct Methods for Sparse Linear Systems

**Timothy A. Davis**

Recommended for graduate students.

Applied Numerical Linear Algebra

**James W. Demmel**

Recommended as a first year graduate textbook for a numerical linear algebra
course.

Learning MATLAB

**Tobin A. Driscoll **

Recommended for advanced undergraduate and graduate students.

Matrix Methods in Data Mining and Pattern Recognition

**Lars Eldén **

Suitable for undergraduate students who have previously taken an introductory scientific computing/numerical analysis course. Graduate students in various data mining and pattern recognition areas who need an introduction to linear algebra techniques will also find the book useful.

-- Sample Chapter

Invariant Subspaces of Matrices with Applications

**Israel Gohberg, Peter Lancaster and Leiba Rodman**

Recommended for readers who have had undergraduate-level courses in linear algebra and complex function theory.

Deblurring Images: Matrices, Spectra, and Filtering

**Per Christian Hansen, James G. Nagy, and Dianne P. O’Leary**

Recommended for beginners in the field of image restoration and regularization.

--Sample Chapter

Numerical Matrix Analysis: Linear Systems and Least Squares

**Ilse C. F. Ipsen
**Recommended for advanced undergraduate and first year graduate students.

Matrix
Analysis for Scientists and Engineers

**Alan J. Laub**

Intended for senior undergraduate and beginning graduate students.

--Sample Chapter

Matrix
Analysis and Applied Linear Algebra

**Carl D. Meyer**

Recommended for undergraduate and beginning graduate courses in applied linear
algebra. Includes CD-ROM and Solution's Manual.

The book can be viewed online at www.matrixanalysis.com.

Iterative Solution of Nonlinear Equations in Several Variables

**J. M. Ortega and W. C. Rheinboldt **

Recommended as an introduction for graduate students.

Iterative
Methods for Sparse Linear Systems, Second Edition

**Yousef Saad**

Recommended for graduate students.

Numerical Methods for Large Eigenvalue Problems, Revised Edition

**Yousef Saad**

Recommended for advanced graduate students.

Numerical
Linear Algebra

**Lloyd N. Trefethen and David Bau, III**

Recommended as an introductory graduate textbook for a numerical linear algebra
course.

## Material Science

Smart Material Systems: Model Development

**Ralph C. Smith**

Recommended for graduate students.

## Numerical Analysis

Computational
Methods for Option Pricing

**Yves Achdou and Olivier Pironneau**

Recommended for advanced graduate students.

Eigenvalues of Matrices, Revised Edition

**Françoise Chatelin**

Recommended for undergraduate students.

Numerical Solution of Algebraic Riccati Equations

**Dario A. Bini, Bruno Iannazzo, and Beatrice Meini**

Recommended for advanced graduate students.

The
SIAM 100-Digit Challenge: A Study in High-Accuracy Numerical Computing

**Folkmar Bornemann, Dirk Laurie, Stan Wagon, and Jörg Waldvogel**

Recommended for graduate students.

Spectral Approximation of Linear Operators

**Françoise Chatelin**

Recommended for advanced undergraduate and graduate students.

The Finite Element Method for Elliptic Problems

**Philippe G. Ciarlet**

Recommended for graduate students.

Numerical Methods in Scientific Computing, *Volume 1*

**Germund Dahlquist, Åke Björck**

Recommended for graduate students.

Collected
Lectures on the Preservation of Stability Under Discretization

**Donald Estep and Simon Tavener, Editors**

Recommended for graduate students.

Numerical Methods for Special Functions

**Amparo Gil, Javier Segura, Nico Temme
**Recommended for general numerical analysis courses.

--Sample Chapter

Discrete Inverse Problems: Insight and Algorithms**
Per Christian Hansen**

Recomended for advanced undergraduate and graduate students.

Functions of Matrices: Theory and Computation

**Nicholas J. Higham**

Recommended for graduate students.

--Sample Chapter

Finite Difference Methods for Ordinary and Partial Differential Equations: Steady-State and Time-Dependent Problems

**Randall J. LeVeque**

Recommended for introductory graduate-level courses.

-- Sample Chapter

Discontinuous Galerkin Methods for Solving Elliptic and Parabolic Equations: Theory and Implementation

**Béatrice Rivière**

Recommended for graduate students.

Afternotes
on Numerical Analysis

**G. W. Stewart**

Recommended as a supplement for an introductory numerical analysis course.

Afternotes
Goes to Graduate School

**G. W. Stewart**

Recommended as a supplemental text for graduate courses in scientific computing
and numerical analysis.

Finite Difference Schemes and Partial Differential Equations, Second Edition

**John C. Strikwerda**

Recommended for gradaute students.

--Sample Chapter

Approximation Theory and Approximation Practice

**Lloyd N. Trefethen**

Recommended for graduate students and advanced undergraduates interested in numerical analysis or approximation theory.

## Optimization

Generalized Concavity

**Mordecai Avriel, Walter E. Diewert, Siegfried Schaible, and Israel Zang**

Recommended for advanced undergraduate and graduate students.

Nonlinear Programming: Concepts, Algorithms, and Applications to Chamical Processes

**Lorenz T. Biegler**

Recommended for advanced undergraduate and graduate students.

Semidefinite Optimization and Convex Algebraic Geometry

**Edited by Grigoriy Blekherman, Pablo A. Parrilo, and Rekha Thomas**

Recommended for advanced undergraduates and first year graduate students.

Computational Optimization of Systems Governed by Partial Differential Equations

**Alfio Borzì and Volker Schulz**

Recommended for graduate students and research colleagues.

Assignment Problems, Revised Reprint

**Rainer Burkard, Mauro Dell'Amico, and Silvano Martello **

Recommended for advanced undergraduate and graduate students.

Introduction to Derivative-Free Optimization

**Andrew R. Conn, Katya Scheinberg, and Luis N. Vicente**

Recommended for advanced undergraduate and graduate students.

Introduction to Optimization and Semidifferential Calculus

**M. C. Delfour**

This book is intended as a textbook for a one-term course in Optimization and Semi-differential Calculus at the undergraduate level for students in Mathematics, Physics, Engineering, Economics, and other disciplines with a basic knowledge of mathematical analysis and linear algebra. The required background material has been added at the end of the first chapter to make the book self-sufficient.

Alternating Projection Methods

**René Escalante and Marcos Raydan**

The book can be used as a textbook for advanced undergraduate or first year graduate students. However, since
the book is comprehensive, it can also be used as a tutorial or a reference by those researchers who need to solve alternating projection problems in their work.

Linear Programming with MATLAB

**Michael C. Ferris, Olvi L. Mangasarian, and Stephen J. Wright **

Recommended for junior- and senior-level undergraduate students, first-year graduate students, and researchers unfamiliar with linear programming.

--Sample Chapter

Methods of Mathematical Economics:
Linear and Nonlinear Programming, Fixed-Point Theorems

**Joel N. Franklin**

Recommended for graduate and undergraduate students of mathematics and
finance.

Linear and Nonlinear Optimization, Second Edition

**Igor Griva, Stephen G. Nash, and Ariela Sofer**

Recommended for advanced undergraduate and graduate students.

Mathematical Optimization and Economic Theory

**Michael D. Intriligator**

Recommended for graduate and undergraduate students of mathematics and
economics.

Implicit Filtering

**C. T. Kelley**

Recommended for students and researchers. Used in applications in electrical, civil, and mechanical engineering.

Iterative Methods for Linear and Nonlinear Equations

**C. T. Kelley**

A PDF file
of this book is available for download. Copyright ©1995 by
the Society for industrial and Applied Mathematics. This electronic
version is for personal use and may not be duplicated or distributed.

Iterative Methods for Optimization

**C. T. Kelley**

A PDF file of
this book is available for download. Copyright ©1999 by
the Society for Industrial and Applied Mathematics. This electronic
version is for personal use and may not be duplicated or distributed.

The Basics of Practical Optimization

Adam B. Levy

Recommended for undergraduate students.

Primer on Optimal Control Theory

Jason L. Speyer and David H. Jacobson

Recommended for undergraduate and first year graduate students.

## Ordinary and Partial Differential Equations

Computer
Methods for Ordinary Differential Equations and Differential-Algebraic Equations

**Uri M. Ascher and Linda R. Petzold**

A first course in the numerical solution of differential equations at either
a senior undergraduate or beginning graduate level.

Linear Ordinary Differential Equations

**Earl A. Coddington and Robert Carlson **

Recommended for graduate and advanced undergraduate students in mathematics, engineering, and science.

A Unified Approach to Boundary Value Problems

**Athanassios S. Fokas
**Recommended for advanced undergraduate and first year graduate students.

Partial Differential Equations: Analytical and Numerical Methods, Second Edition

**Mark S. Gockenbach**

Recommended for graduate students in applied mathematics and for undergradate
and graduate students in engineering and physics.

Understanding and Implementing the Finite Element Method

**Mark S. Gockenbach**

Recommended for advanced undergraduates and beginning graduate students in mathematics, engineering, and the physical sciences.

-- Sample Chapter

Ordinary
Differential Equations: Second Edition

**Philip Hartman**

Recommended for advanced undergraduate and graduate students in mathematics,
physics, and engineering.

Physics and Partial Differential Equations, Volume I

**Tatsien Li and Tiehu Qin, Translated by Yachun Li**

Recommended for upper-level undergraduate and graduate courses.

Partial
Differential Equations: Modeling, Analysis, Computation

**R. M. M. Matthiej, S. W. Rienstra, and J. M. M. ten Thije Boonkamp**

Recommended for advanced undergraduate and graduate students.

-- Sample Chapter

Perturbations: Theory and Methods

**James A. Murdock**

This text can be used before or after a traditional graduate course in ordinary differential equations.

## Physical Applied Mathematics and Mathematical Modeling

Lectures on Mathematical Combustion

**John D. Buckmaster and Geoffrey S. S. Ludford**

Dynamics of Internal Layers and Diffusive Interfaces

**Paul C. Fife**

The Cauchy Problem in Kinetic Theory

**Robert T. Glassey**

Suitable for advanced graduate students.

Continuum Modeling in the Physical Sciences

**E. van Groesen and Jaap Molenaar**

Recommended for graduate students and advanced undergraduate students.

-- Sample Chapter

Mathematical Models: Mechanical Vibrations, Population Dynamics, and Traffic Flow

**Richard Haberman**

Mathematical Modeling: Classroom Notes in Applied Mathematics

**Murray S. Klamkin, Editor**

Mathematics Applied to Continuum Mechanics

**Lee A. Segel with additional material on elasticity by G. H. Handelman **

This is an ideal text for upper-level undergraduate and graduate students in the fields of applied mathematics, science, and engineering.

Mathematics Applied to Deterministic Problems in the Natural Sciences

**C.C. Lin and L.A Segel**

Boundary Value Problems of Mathematical Physics

**Ivar Stakgold**

Suitable for introductory level graduate courses.

## Probability and Statistics

Anthology
of Statistics in Sports

**Jim Albert, Jay Bennett, and James L. Cochran, Editors**

Recommended as supplementary material for statistics courses.

A First Course in Order Statistics

**Barry C. Arnold, N. Balakrishnan, H. N. Nagaraja **

Recommended for advanced undergraduate and graduate students in Statistics and Mathematics.

Mathematica Laboratories for Mathematical Statistics: Emphasizing Simulation and Computer
Intensive Methods

**Jenny Baglivo**

Recommended for undergraduate students. Techniques are accessible to students
with little or no experience with Mathematica.

-- Sample Chapter

-- Sample Lab from
CD

Engineering
Reliability

**Richard E. Barlow**

Recommended for an upper undergraduate or beginning graduate course on engineering
reliability. Instructor Manual available upon request.

Probability

**Leo Breiman**

Recommended for use as a graduate-level text in one- or two-semester courses in probability for students who are familiar with basic measure theory, or as a supplement in courses in stochastic processes or mathematical statistics.

Selection and Ordering Populations: A New Statistical Methodology

**Jean Dickinson Gibbons, Ingram Olkin, and Milton Sobel**

Suitable for students with a first-year knowledge of statistics.

Basic
Concepts of Probablility and Statistics, Second Edition

**J. L. Hodges, Jr. and E. L. Lehmann**

Recommended for high school and undergraduate students

Introduction to Matrix Analytic Methods in Stochastic Modeling

**G. Latouche and V. Ramaswami**

Recommended for graduate students and advanced undergraduates.

The
Analysis of Means: A Graphical Method for Comparing Means, Rates, and Proportions

**Peter R. Nelson, Peter S. Wludyka, and Karen A. F. Copeland**

Recommended for graduate students.

-- Sample Chapter

Applied
Adaptive Statistical Methods: Tests of Significance and Confidence Intervals

**Thomas W. O'Gorman**

Recommended as a supplementary text in a course on regression analysis.

Stochastic Processes

**Emanuel Parzen**

Suitable for an introductory course on probability model building.

Statistical
Case Studies: A Collaboration Between Academe and Industry

**Roxy Peck, Larry D. Haugh, and Arnold Goodman**

Recommended for a statistical consulting course and as a supplement to any
statistics course.

Optimal Design of Experiments

**Friedrich Pukelsheim**

Indispensible for anyone involved in planning statistical experiments, including mathematical statisticians, applied statisticians, and mathematicians interested in matrix optimization problems.

Fuzzy
Logic and Probability Applications: Bridging the Gap

**Timothy J. Ross, Jane M. Booker, and W. Jerry Parkinson, Editors**

-- Sample Chapter

## Real and Complex Analysis

Functions of a Complex Variable: Theory and Technique

**George F. Carrier, Max Krook, and Carl E. Pearson**

Recommended for graduate students and advanced undergraduate students.

Numerical Methods for Special Functions

**Amparo Gil, Javier Segura, Nico Temme
**Recommended for general numerical analysis courses.

--Sample Chapter

## Simulation and Modeling

Computational Mathematical Modeling: An Integrated Approach Across Scales

**Daniela Calvetti and Erkki Somersalo**

This book is intended for advanced undergraduate and beginning graduate students in mathematics, engineering, and physical and life sciences.

Modeling, Simulation, and Optimization of Supply Chains: A Continuous Approach**
Ciro D'Apice, Simone Göttlich, Michael Herty, and Benedetto Piccoli
**Recommended for advanced undergraduate and graduate students.

Uncertainty Quantification: Theory, Implementation, and Applications

**Ralph Smith**

Recommended for advanced undergraduates, graduate students, and researchers in mathematics, statistics, operations research, computer science, biology, science, and engineering.

## Waves

Solitons and the Inverse Scattering Transform

**Mark J. Ablowitz and Harvey Segur**

Solitons in Mathematics and Physics

**Alan C. Newell**

Nonlinear Waves in Integrable and Nonintegrable Systems

**Jianke Yang**

Recommended for advanced graduate students.