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Computational Bayesian Statistics
This integrated introduction to fundamentals, computation, and software is your key to understanding and using advanced Bayesian methods.
Exponential Families in Theory and Practice
During the past half-century, exponential families have attained a position at the center of parametric statistical inference. Theoretical advances have been matched, and more than matched, in the world of applications, where logistic regression by itself has become the go-to methodology in medical statistics, computer-based prediction algorithms, and the social sciences. This book is based on a one-semester graduate course for first year Ph.D. and advanced master's students. After presenting the basic structure of univariate and multivariate exponential families, their application to generalized linear models including logistic and Poisson regression is described in detail, emphasizing geometrical ideas, computational practice, and the analogy with ordinary linear regression. Connections are made with a variety of current statistical methodologies: missing data, survival analysis and proportional hazards, false discovery rates, bootstrapping, and empirical Bayes analysis. The book connects exponential family theory with its applications in a way that doesn't require advanced mathematical preparation.
Bayesian Filtering and Smoothing
A Bayesian treatment of the state-of-the-art filtering, smoothing, and parameter estimation algorithms for non-linear state space models.
Statistical Modelling by Exponential Families
A readable, digestible introduction to essential theory and wealth of applications, with a vast set of examples and numerous exercises.
New Advances in Statistical Modeling and Applications
This volume of the Selected Papers is a product of the XIX Congress of the Portuguese Statistical Society, held at the Portuguese town of Nazaré, from September 28 to October 1, 2011. All contributions were selected after a thorough peer-review process. It covers a broad scope of papers in the areas of Statistical Science, Probability and Stochastic Processes, Extremes and Statistical Applications.
Principles of Statistical Analysis
This concise course in data analysis and inference for the mathematically literate builds on survey sampling and designed experiments.
Advances in Regression, Survival Analysis, Extreme Values, Markov Processes and Other Statistical Applications
This volume of the Selected Papers from Portugal is a product of the Seventeenth Congress of the Portuguese Statistical Society, held at the beautiful resort seaside city of Sesimbra, Portugal, from September 30 to October 3, 2009. It covers a broad scope of theoretical, methodological as well as application-oriented articles in domains such as: Linear Models and Regression, Survival Analysis, Extreme Value Theory, Statistics of Diffusions, Markov Processes and other Statistical Applications.
Two-Dimensional Random Walk
A visual, intuitive introduction in the form of a tour with side-quests, using direct probabilistic insight rather than technical tools.
Scheduling and Control of Queueing Networks
A graduate text on theory and methods using applied probability techniques for scheduling service, manufacturing, and information networks.
An Introduction to Categorical Data Analysis
A valuable new edition of a standard reference The use of statistical methods for categorical data has increased dramatically, particularly for applications in the biomedical and social sciences. An Introduction to Categorical Data Analysis, Third Edition summarizes these methods and shows readers how to use them using software. Readers will find a unified generalized linear models approach that connects logistic regression and loglinear models for discrete data with normal regression for continuous data. Adding to the value in the new edition is: • Illustrations of the use of R software to perform all the analyses in the book • A new chapter on alternative methods for categorical data, ...
