Computational Statistics, Second Edition. Author(s). Geof H. Givens · Jennifer A. Hoeting. First published March Print ISBN |Online. Computational Statistics by Geof H. Givens; Jennifer A. Hoeting. Review by: Galin L. Jones. Journal of the American Statistical Association, Vol. Computational Statistics, 2nd Edition. by Jennifer A. Hoeting, Geof H. Givens. Publisher: John Wiley & Sons. Release Date: November
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This new edition continues to serve as a comprehensive guide to modern and classical methods of statistical computing. The book is comprised of four main parts spanning the field:.
Within these sections, each chapter includes a comprehensive introduction and step-by-step implementation summaries to accompany the explanations of key methods. The new edition includes updated coverage and existing topics as well as new topics such as adaptive MCMC and bootstrapping for correlated data.
The book website now includes comprehensive R code for the entire book.
Computational statistics – Geof H. Givens, Jennifer Ann Hoeting – Google Books
There comutational extensive exercises, real examples, and helpful insights about how to use the methods in practice. Stay ahead with the world’s most comprehensive technology and business learning platform.
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Computational Statistics: Geof H. Givens, Jennifer A. Hoeting: : Books
Start Free Trial No credit card required. Computational Statistics, 2nd Edition by Jennifer A. View table of contents.
Book Description This new edition continues to serve as a comprehensive guide to modern and classical methods of statistical computing. The book is comprised of four main parts spanning the givenss Optimization Integration and Simulation Bootstrapping Density Estimation and Smoothing Within these sections, each chapter includes a comprehensive introduction and step-by-step implementation summaries to accompany the explanations of key methods.
The ebook version does not provide access to the companion files.
Computational Statistics, 2nd Edition
Optimization and Solving Nonlinear Equations 2. Em Optimization Methods 4. Integration and Simulation Chapter 5: Simulation stagistics Monte Carlo Integration 6. Markov Chain Monte Carlo 7. Density Estimation and Smoothing Chapter Nonparametric Density Estimation