Introducing Monte Carlo Methods with R.

Autor/inn/en	Robert, Christian P.; Casella, George
Titel	Introducing Monte Carlo Methods with R.
Quelle	New York, NY u.a.: Springer (2010), XIX, 283 S. PDF als Volltext Link als defekt meldenVerfügbarkeit
Reihe	Use R!; Statistics
Beigaben	grafische Darstellungen; Literaturangaben S. [269]-274
Zusatzinformation	Inhaltsverzeichnis Inhaltsangabe
Sprache	englisch
Dokumenttyp	online; gedruckt; Monographie
ISBN	1-4419-1575-3; 978-1-4419-1575-7
DOI	10.1007/978-1-4419-1576-4
Schlagwörter	Lehrbuch; Algorithmus; Programmiersprache; Messverfahren; Statistik; Daten; Simulation; Statistische Methode
Abstract	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. 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. ... The book covers basic random generation algorithms, Monte Carlo techniques for integration and optimization, convergence diagnoses, Markov chain Monte Carlo methods, including Metropolis {Hastings and Gibbs algorithms, and adaptive algorithms). All chapters include exercises and all R programs are available as an R package called mcsm. (DIPF/Orig.).
Erfasst von	DIPF \| Leibniz-Institut für Bildungsforschung und Bildungsinformation, Frankfurt am Main
Update	2011/4