Modeling with Data: Tools and Techniques for Scientific Computing
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. Get and download textbook Modeling with Data: Tools and Techniques for Scientific Computing for free
Categories: Mathematical models, Mathematical statistics. Contributors: Ben Klemens - Author. Format: Hardcover
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 mod Modeling with Data new edition
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author ben klemens format hardback language english publication year 06 10 2008 subject computing it subject 2 software packages title modeling with data tools and techniques for scientific computing author ben klemens publisher princeton university press publication date nov 06 2008 pages 470 binding hardcover edition illustrated dimensions 7 00 wx 10 00 hx 1 25 d isbn 069113314 x subject mathematics probability statistics general description modeling with data fully explains how to execute c
How do we make the field and laboratory coherent? How do we use statistics to help experimentation? How do we integrate modeling and statistics? This book answers these questions. It makes liberal use of computer programming for the generation of hypotheses, exploration of data, and the comparison of different models.
The modern ecologist usually works in both the field and laboratory, uses statistics and computers, and often works with ecological concepts that are model-based, if not model-driven. How do we make the field and laboratory coherent? How do we link models and data? How do we use statistics to help experimentation? How do we integrate modeling and statistics? How do we confront multiple hypotheses with data and assign degrees of belief to different hypotheses? How do we deal with time series (in which data are linked from one measurement to the next) or put multiple sources of data into one inf
Categories: Ecology->Mathematical models. Contributors: Ray Hilborn - Author. Format: Paperback
Modeling with Data Textbook
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
Klemens's accessible survey describes these mod
