**Modeling with Data: Tools and Techniques for Scientific Computing**

by Ben Klemens

**Publisher**: Princeton University Press 2009**ISBN/ASIN**: 069113314X**ISBN-13**: 9780691133140**Number of pages**: 470

**Description**:

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.

Download or read it online for free here:

**Download link**

(4.3MB, PDF)

## Similar books

**Fuzzy Systems**

by

**Ahmad Taher Azar**-

**InTech**

This book is intended to present fuzzy logic systems and useful applications with a simple approach. It is written at a level suitable for use in a graduate course on applications of fuzzy systems in decision support, nonlinear modeling and control.

(

**11717**views)

**Physical Modeling in MATLAB**

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.

(

**16314**views)

**The Nature of Code: Simulating Natural Systems with Processing**

by

**Daniel Shiffman**-

**The Nature of Code**

This book focuses on a range of programming strategies and techniques behind computer simulations of natural systems, from elementary concepts in mathematics and physics to more advanced algorithms that enable sophisticated visual results.

(

**12099**views)

**Computer Simulation Techniques - The Definitive Introduction**

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.

(

**16442**views)