Suitable for a first year graduate course, this textbook unites the applications of numerical mathematics and scientific computing to the practice of chemical engineering. Written in a pedagogic style, the book describes basic linear and nonlinear algebric systems all the way through to stochastic methods, Bayesian statistics and parameter...

As modern devices, from cell phones to airplanes, become lighter and more flexible, vibration suppression and analysis becomes more critical. Vibration with Control, 2^nd Edition includes modelling,...

"I highly recommend the book; treat yourself to it; assign it toa class; give it as a gift."
—The...

Data Analysis Using Regression and Multilevel/Hierarchical Models is a comprehensive manual for the applied researcher who wants to perform data analysis using linear and nonlinear regression and multilevel models. The book introduces a wide variety of models, whilst at the same time instructing the reader in how to fit these models using...

Bayesian inference provides a simple and unified approach to data analysis, allowing experimenters to assign probabilities to competing hypotheses of interest, on the basis of the current state of knowledge. By incorporating relevant prior information, it can sometimes improve model parameter estimates by many orders of magnitude. This book...

Driven by concrete computational problems in quantitative finance, this book provides aspiring quant developers with the numerical techniques and programming skills they need. The authors start from scratch, so the reader does not need any previous experience of C++. Beginning with straightforward option pricing on binomial trees, the book...

This second edition textbook describes the design and implementation of high-performance feedback controllers for engineering systems. It emphasizes the frequency-domain design and methods based on Bode integrals, loop shaping, and nonlinear dynamic compensation. The authors include many problems and offer practical applications,...