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β¦ Synopsis
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.Β Sampling-based simulation techniques are now an invaluable tool for exploring statistical models.Β 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.Β 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 environmentΒ 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.Β 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
β Jochen Vossπ Libraryπ 2013π Wileyπ English
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 s
β M. M. Woolfson, G. J. Pertπ Libraryπ 1999π Oxford University Press, USAπ English
For every mathematician working with complex physic tests and a limited budget, this book can be useful. Unfortunately I am just a modeler of simple discrete event simulations, so for me this book was not very useful. Except for the first chapter that tells a little about different simulation metho
β M. M. Woolfson, G. J. Pertπ Libraryπ 1999π Oxford University Press, USAπ English
Computer simulation is increasingly used in physics and engineering to predict the probable outcome of experiments and to aid in their interpretation. The methods of simulation are based on a range of numerical techniques for treating ordinary and partial differential equations. Since much of phys
β M. M. Woolfson, G. J. Pertπ Libraryπ 1999π Oxford University Pressπ English
Computer simulation is increasingly used in physics and engineering to predict the probable outcome of experiments and to aid in their interpretation. This text for undergraduates illustrates the basic techniques with numerous simple programs and problems drawn from a wide range of disciplines.
β Shravan Vasishth, Michael Broe (auth.)π Libraryπ 2011π Springer-Verlag Berlin Heidelbergπ English
<p><p>Statistics and hypothesis testing are routinely used in areas (such as linguistics) that are traditionally not mathematically intensive. In such fields, when faced with experimental data, many students and researchers tend to rely on commercial packages to carry out statistical data analysis,
β Shravan Vasishth, Michael Broe (auth.)π Libraryπ 2011π Springer-Verlag Berlin Heidelbergπ English
<p><p>Statistics and hypothesis testing are routinely used in areas (such as linguistics) that are traditionally not mathematically intensive. In such fields, when faced with experimental data, many students and researchers tend to rely on commercial packages to carry out statistical data analysis,