Using R for Numerical Analysis in Science and Engineering

Bloomfield, Victor A.

ISBN 10: 143988448X / ISBN 13: 9781439884485

Verlag: Chapman and Hall/CRC, 2014

Beschreibung

Bestandsnummer des Verkäufers 20898350-n

Bibliografische Details

Titel: Using R for Numerical Analysis in Science ...

Verlag: Chapman and Hall/CRC

Erscheinungsdatum: 2014

Einband: Hardcover

Zustand: New

Über diesen Titel

Inhaltsangabe:

<PINSTEAD OF PRESENTING THE STANDARD THEORETICAL TREATMENTS THAT UNDERLIE THE VARIOUS NUMERICAL METHODS USED BY SCIENTISTS AND ENGINEERS, <BUSING R FOR NUMERICAL ANALYSIS IN SCIENCE AND ENGINEERING</B SHOWS HOW TO USE R AND ITS ADD-ON PACKAGES TO OBTAIN NUMERICAL SOLUTIONS TO THE COMPLEX MATHEMATICAL PROBLEMS COMMONLY FACED BY SCIENTISTS AND ENGINEERS. THIS PRACTICAL GUIDE TO THE CAPABILITIES OF R DEMONSTRATES MONTE CARLO, STOCHASTIC, DETERMINISTIC, AND OTHER NUMERICAL METHODS THROUGH AN ABUNDANCE OF WORKED EXAMPLES AND CODE, COVERING THE SOLUTION OF SYSTEMS OF LINEAR ALGEBRAIC EQUATIONS AND NONLINEAR EQUATIONS AS WELL AS ORDINARY DIFFERENTIAL EQUATIONS AND PARTIAL DIFFERENTIAL EQUATIONS. IT NOT ONLY SHOWS HOW TO USE R’S POWERFUL GRAPHIC TOOLS TO CONSTRUCT THE TYPES OF PLOTS MOST USEFUL IN SCIENTIFIC AND ENGINEERING WORK, BUT ALSO:</P <UL <P <LIEXPLAINS HOW TO STATISTICALLY ANALYZE AND FIT DATA TO LINEAR AND NONLINEAR MODELS</LI <LIEXPLORES NUMERICAL DIFFERENTIATION, INTEGRATION, AND OPTIMIZATION</LI <LIDESCRIBES HOW TO FIND EIGENVALUES AND EIGENFUNCTIONS</LI <LIDISCUSSES INTERPOLATION AND CURVE FITTING</LI <LICONSIDERS THE ANALYSIS OF TIME SERIES</LI <P</P</UL<B <PUSING R FOR NUMERICAL ANALYSIS IN SCIENCE AND ENGINEERING</B PROVIDES A SOLID INTRODUCTION TO THE MOST USEFUL NUMERICAL METHODS FOR SCIENTIFIC AND ENGINEERING DATA ANALYSIS USING R.</P

Críticas:

"... the book is well organized, clearly written, and has a large amount of useful R code. It does a good job of answering the question of how to use R to perform numerical analyses of interest to scientists and engineers and, as such, can be recommended to the intended audience."
―Journal of the Royal Statistical Society, Series A, 2015

"I would recommend it to those seeking to improve their programming efficiency. ... the extensive coverage of optimization, ordinary differential equations, and partial differential equations combined with its exemplary demonstration of R coding through effective examples make this book a valuable resource for a wide audience. ... a good reference for scientific and engineering researchers."
―The American Statistician, February 2015

"... the book is well organized, clearly written, and has a large amount of useful R code. It does a good job answering the question of how to use R to perform numerical analyses of interest to scientists and engineers, and as such, can be recommended to the intended audience."
―Andrey Kostenko, Teaching Statistics