An Introduction to Statistical Computing

A Simulation-based Approach de

Éditeur :

Wiley


Collection :

Wiley Series in Computational Statistics

Paru le : 2013-08-28

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Description
A comprehensive introduction to sampling-based methods in statistical computing
The use of computers in mathematics and statistics has opened up a wide range of techniques for studying otherwise intractable problems. Sampling-based simulation techniques are now an invaluable tool for exploring statistical models. This book gives a comprehensive introduction to the exciting area of sampling-based methods.
An Introduction to Statistical Computing introduces the classical topics of random number generation and Monte Carlo methods. It also includes some advanced methods such as the reversible jump Markov chain Monte Carlo algorithm and modern methods such as approximate Bayesian computation and multilevel Monte Carlo techniques
An Introduction to Statistical Computing: Fully covers the traditional topics of statistical computing. Discusses both practical aspects and the theoretical background. Includes a chapter about continuous-time models. Illustrates all methods using examples and exercises. Provides answers to the exercises (using the statistical computing environment R); the corresponding source code is available online. Includes an introduction to programming in R.
This book is mostly self-contained; the only prerequisites are basic knowledge of probability up to the law of large numbers. Careful presentation and examples make this book accessible to a wide range of students and suitable for self-study or as the basis of a taught course.
Pages
400 pages
Collection
Wiley Series in Computational Statistics
Parution
2013-08-28
Marque
Wiley
EAN papier
9781118357729
EAN PDF
9781118728031

Informations sur l'ebook
Nombre pages copiables
0
Nombre pages imprimables
400
Taille du fichier
6451 Ko
Prix
79,07 €
EAN EPUB
9781118728024

Informations sur l'ebook
Nombre pages copiables
0
Nombre pages imprimables
400
Taille du fichier
9523 Ko
Prix
79,07 €