Kategoria BISAC: Mathematics >> Probability & Statistics - Bayesian Analysis

Bayesian Analysis with Stata is written for anyone interested in applying Bayesian methods to real data easily. The book shows how modern analyses based on Markov chain Monte Carlo (MCMC) methods are implemented in Stata both directly and by passing Stata datasets to OpenBUGS or WinBUGS for computation, allowing Stata s data management and graphing capability to be used with OpenBUGS/WinBUGS speed and reliability.

The book emphasizes practical data analysis from the Bayesian perspective, and hence covers the selection of realistic priors, computational...

Infolge der ausgesprochen positiven Aufnahme dieses Lehrbuches liegt nun die 5. Auflage vor. Das Buch gibt eine Einfuhrung in die zentralen Ideen und Ergebnisse der Wahrscheinlichkeitstheorie und Statistik. Die stochastischen Konzepte, Modelle und Methoden werden durch typische Anwendungsbeispiele motiviert und anschlieend theoretisch analysiert und systematisch entwickelt.

Cohesively Incorporates Statistical Theory with R Implementation

Since the publication of the popular first edition of this comprehensive textbook, the contributed R packages on CRAN have increased from around 1,000 to over 6,000. Designed for an intermediate undergraduate course, Probability and Statistics with R, Second Edition explores how some of these new packages make analysis easier and more intuitive as well as create more visually pleasing graphs.

New to the Second Edition

• Improvements to existing examples, problems,...

Learn How to Infuse Leadership into Your Passion for Scientific Research

Leadership and Women in Statistics explores the role of statisticians as leaders, with particular attention to women statisticians as leaders. By paying special attention to women s issues, this book provides a clear vision for the future of women as leaders in scientific and technical fields. It also shows how emerging and current leaders of both genders in many disciplines can expand their leadership potentials.

Featuring contributions from leadership experts and statisticians at various career stages, this...

Stochastic Analysis for Gaussian Random Processes and Fields: With Applications presents Hilbert space methods to study deep analytic properties connecting probabilistic notions. In particular, it studies Gaussian random fields using reproducing kernel Hilbert spaces (RKHSs).

The book begins with preliminary results on covariance and associated RKHS before introducing the Gaussian process and Gaussian random fields. The authors use chaos expansion to define the Skorokhod integral, which generalizes the Ito integral. They show how the Skorokhod integral is a...