Modeling with Data: Tools and Techniques for Scientific Computing
by Ben Klemens
Publisher: Princeton University Press 2009
Number of pages: 470
The book fully explains how to execute computationally intensive analysis on very large data sets, showing readers how to determine the best methods for solving a variety of different problems, how to create and debug statistical models, and how to run an analysis and evaluate the results. Ben Klemens introduces a set of open and unlimited tools, and uses them to demonstrate data management, analysis, and simulation techniques essential for dealing with large data sets and computationally intensive procedures. Modeling with Data will interest anyone looking for a comprehensive guide to these powerful statistical tools, including researchers and graduate students in the social sciences, biology, engineering, economics, and applied mathematics.
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by Harry Perros - NC State University
The generation of pseudo-random numbers, the generation of stochastic variates, simulation designs, estimation techniques for analyzing endogenously created data, validation of a simulation model, variance reduction techniques, etc.
by N. I. Badler, C. B. Phillips, B. L. Webber - Oxford University Press, USA
This volume presents the problem of providing a surrogate or synthetic human for designers and engineers. The book is intended for engineers interested in understanding how a computer surrogate human can augment their analyses of designed environments.
by Allen Downey - Green Tea Press
An introductory textbook for people who have not programmed before. Covers basic MATLAB programming with emphasis on modeling and simulation of physical systems. The book starts with scalar values and works up to vectors and matrices very gradually.
This book helps you to start modeling with AnyLogic -- a multi-method simulation modeling tool that supports different modeling techniques. Topics covered: Agent-Based Modeling; System Dynamics; Discrete Event Simulation; Pedestrian Simulation.