Introducing Monte Carlo Methods with R

This book PDF is perfect for those who love Computers genre, written by Christian Robert and published by Springer Science & Business Media which was released on 28 March 2024 with total hardcover pages 297. You could read this book directly on your devices with pdf, epub and kindle format, check detail and related Introducing Monte Carlo Methods with R books below.

Introducing Monte Carlo Methods with R
Author : Christian Robert
File Size : 55,9 Mb
Publisher : Springer Science & Business Media
Language : English
Release Date : 28 March 2024
ISBN : 9781441915757
Pages : 297 pages
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Introducing Monte Carlo Methods with R by Christian Robert Book PDF Summary

This book covers the main tools used in statistical simulation from a programmer’s point of view, explaining the R implementation of each simulation technique and providing the output for better understanding and comparison.

Introducing Monte Carlo Methods with R

This book covers the main tools used in statistical simulation from a programmer’s point of view, explaining the R implementation of each simulation technique and providing the output for better understanding and comparison.

Get Book
Introducing Monte Carlo Methods with R

Computational techniques based on simulation have now become an essential part of the statistician's toolbox. It is thus crucial to provide statisticians with a practical understanding of those methods, and there is no better way to develop intuition and skills for simulation than to use simulation to solve statistical problems.

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Introducing Monte Carlo Methods with R

Download or read online Introducing Monte Carlo Methods with R written by Christian P. Robert,George Casella, published by Unknown which was released on 2010-04-17. Get Introducing Monte Carlo Methods with R Books now! Available in PDF, ePub and Kindle.

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Monte Carlo Statistical Methods

We have sold 4300 copies worldwide of the first edition (1999). This new edition contains five completely new chapters covering new developments.

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Handbook of Markov Chain Monte Carlo

Since their popularization in the 1990s, Markov chain Monte Carlo (MCMC) methods have revolutionized statistical computing and have had an especially profound impact on the practice of Bayesian statistics. Furthermore, MCMC methods have enabled the development and use of intricate models in an astonishing array of disciplines as diverse as

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Monte Carlo Simulation and Resampling Methods for Social Science

Taking the topics of a quantitative methodology course and illustrating them through Monte Carlo simulation, Monte Carlo Simulation and Resampling Methods for Social Science, by Thomas M. Carsey and Jeffrey J. Harden, examines abstract principles, such as bias, efficiency, and measures of uncertainty in an intuitive, visual way. Instead of

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Handbook of Monte Carlo Methods

A comprehensive overview of Monte Carlo simulation that explores the latest topics, techniques, and real-world applications More and more of today’s numerical problems found in engineering and finance are solved through Monte Carlo methods. The heightened popularity of these methods and their continuing development makes it important for researchers

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Sequential Monte Carlo Methods in Practice

Monte Carlo methods are revolutionizing the on-line analysis of data in many fileds. They have made it possible to solve numerically many complex, non-standard problems that were previously intractable. This book presents the first comprehensive treatment of these techniques.

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