Modeling with Data (eBook)

Tools and Techniques for Scientific Computing

Ben Klemens (Autor)

eBook Download: PDF

2008
472 Seiten
Princeton University Press (Verlag)
978-1-4008-2874-6 (ISBN)

Infos

Modeling with Data fully explains how to execute computationally intensive analyses 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. He then demonstrates how to easily apply these tools to the many threads of statistical technique, including classical, Bayesian, maximum likelihood, and Monte Carlo methods. Klemens's accessible survey describes these models in a unified and nontraditional manner, providing alternative ways of looking at statistical concepts that often befuddle students. The book includes nearly one hundred sample programs of all kinds. Links to these programs will be available on this page at a later date. 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.

Autor

Ben Klemens is a senior statistician at the National Institute of Mental Health. He is also a guest scholar at the Center on Social and Economic Dynamics at the Brookings Institution.

Produkt-Details

• Erscheint lt. Verlag: 6.10.2008
• Zusatzinfo: 35 line illus. 16 tables.
• Verlagsort: Princeton
• Sprache: englisch
• Themenwelt: Informatik ► Datenbanken ► Data Warehouse / Data Mining
• Themenwelt: Mathematik / Informatik ► Informatik ► Software Entwicklung
• Themenwelt: Mathematik / Informatik ► Mathematik ► Computerprogramme / Computeralgebra
• Themenwelt: Naturwissenschaften
• Themenwelt: Technik
• Schlagworte: apophenia • Arbitrary-precision arithmetic • Assertion (software development) • binary tree • Binomial Distribution • Bootstrapping (statistics) • C99 • Calculation • central limit theorem • Chi-squared test • Command-line interface • Compiler • Conditional (computer programming) • Conjugate Gradient Method • Convenience function • Cook's Distance • Count Data • Counting • Cramér–Rao bound • C syntax • Database • data set • Debugger • Dummy variable (statistics) • Environment variable • Error Term • estimation • executable • expected value • Fisher Information • Fisher's Exact Test • For loop • F-Test • glib • GNUPLOT • Grep • histogram • Include directive • Indent style • Integer • Integer overflow • Least Squares • Likelihood Function • Likelihood-ratio test • Linker (computing) • Listwise deletion • Local variable • Logistic Regression • Logit • Long filename • Makefile • Mathematical Optimization • maximum likelihood estimation • missing data • Monte Carlo Method • Naming convention (programming) • negative binomial distribution • Newline • Newton's method • Normal distribution • Null pointer • Object file • one-way analysis of variance • order of operations • Ordinary Least Squares • pairwise • Parameter (computer programming) • Pattern Matching • Preprocessor • Probability • probit • Pseudocode • Ranking (information retrieval) • Regular Expression • Root-finding algorithm • Run time (program lifecycle phase) • Segmentation fault • semicolon • Sentinel value • Significant figures • sizeof • Source lines of code • Special case • SQL • SQLite • Standard streams • Static variable • Statistic • String literal • Struct (C programming language) • Student's t-test • Subset • summary statistics • text processing • Type I and type II errors • unique key • Variable (computer science) • Variable (mathematics) • Variance • Void type
• ISBN-10: 1-4008-2874-0 / 1400828740
• ISBN-13: 978-1-4008-2874-6 / 9781400828746