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

Based on the author s course at NYU, Linear Algebra and Probability for Computer Science Applications" "gives an introduction to two mathematical fields that are fundamental in many areas of computer science. The course and the text are addressed to students with a very weak mathematical background. Most of the chapters discuss relevant MATLAB(r) functions and features and give sample assignments in MATLAB; the author s website provides the MATLAB code from the book.

After an introductory chapter on MATLAB, the text is divided into two sections. The section on linear algebra gives an...

This book gives a reliable review on structure selection of stochastic dynamic systems using information criteria AIC, BIC, o and stochastic complexity. After theoretical investigations many simulations are estimators, which illustrate both the effectiveness and the limitations of these methods. The reader can gain his or her own experience on the"working" of many methods (associated with different parameter estimators) using the demonstration disk which can be run on most IBM-compatible personal computers. The book will be helpful to anybody interested in applying automated methods of...

Praise for the Second Edition
"This book should be an essential part of the personal library of every practicing statistician."--Technometrics

Thoroughly revised and updated, the new edition of Nonparametric Statistical Methods includes additional modern topics and procedures, more practical data sets, and new problems from real-life situations. The book continues to emphasize the importance of nonparametric methods as a significant branch of modern statistics and equips readers with the conceptual and technical skills necessary to select and apply the...

One of the main issues in communications theory is measuring the ultimate data compression possible using the concept of entropy. While differential entropy may seem to be a simple extension of the discrete case, it is a more complex measure that often requires a more careful treatment.

Handbook of Differential Entropy provides a comprehensive introduction to the subject for researchers and students in information theory. Unlike related books, this one brings together background material, derivations, and applications of differential entropy.

The...

Based on the author's extensive work, research and presentations in the area, the book fills a gap in quantitative risk management by introducing a new and very intuitively appealing approach to stress testing based on expert judgement and Bayesian networks. It constitutes a radical departure from the traditional statistical methodologies based on Economic Capital or Extreme-Value-Theory...

Already popular in the analysis of medical device trials, adaptive Bayesian designs are increasingly being used in drug development for a wide variety of diseases and conditions, from Alzheimer s disease and multiple sclerosis to obesity, diabetes, hepatitis C, and HIV. Written by leading pioneers of Bayesian clinical trial designs, Bayesian Adaptive Methods for Clinical Trials explores the growing role of Bayesian thinking in the rapidly changing world of clinical trial analysis.

The book first summarizes the current state of clinical trial design and...

A modern and practical guide to the essential concepts and ideas for analyzing data with missing observations in the field of biostatistics

With an emphasis on hands-on applications, Applied Missing Data Analysis in the Health Sciences outlines the various modern statistical methods for the analysis of missing data. The authors acknowledge the limitations of established techniques and provide newly-developed methods with concrete applications in areas such as causal inference methods and the field of diagnostic medicine.

Organized by types of data, chapter...

This book summarizes the results of various models under normal theory with a brief review of the literature. Statistical Inference for Models with Multivariate t-Distributed Errors

• Includes a wide array of applications for the analysis of multivariate observations
• Emphasizes the development of linear statistical models with applications to engineering, the physical sciences, and mathematics
• Contains an up-to-date bibliography featuring the latest trends and advances in the field to provide a collective source for research on the topic
...

Discrete phenomena are an important aspect of various complex systems, acting both as underlying driving mechanisms and as manifestations of diverse behaviours. However, the characterisation of these discrete phenomena requires models that go beyond those featured in existing books.

Largely concerned with mathematical models used to describe time-varying populations and series of events, The Dynamics of Discrete Populations and Series of Events demonstrates how analytical tools are used to develop, simulate, and solve discrete stochastic models. It provides an...

Recursive Identification and Parameter Estimation describes a recursive approach to solving system identification and parameter estimation problems arising from diverse areas. Supplying rigorous theoretical analysis, it presents the material and proposed algorithms in a manner that makes it easy to understand providing readers with the modeling and identification skills required for successful theoretical research and effective application.
The book begins by introducing the basic concepts of probability theory, including martingales, martingale difference sequences, Markov...

Explore Theory and Techniques to Solve Physical, Biological, and Financial Problems

Since the first edition was published, there has been a surge of interest in stochastic partial differential equations (PDEs) driven by the Levy type of noise. Stochastic Partial Differential Equations, Second Edition incorporates these recent developments and improves the presentation of material.

New to the Second Edition

• Two sections on the Levy type of stochastic integrals and the related stochastic differential equations in...

You're outnumbered, in fear for your life, surrounded by flesheating zombies. What can save you now? Mathematics, of course.

Mathematical Modelling of Zombies engages the imagination to illustrate the power of mathematical modelling. Using zombies as a "hook," you'll learn how mathematics can predict the unpredictable. In order to be prepared for the apocalypse, you'll need mathematical models, differential equations, statistical estimations, discretetime models, and adaptive strategies for zombie attacks--as well as baseball bats and Dire Straits records (latter two items not...

The growing interest in using combination drugs to treat various complex diseases has spawned the development of many novel statistical methodologies. The theoretical development, coupled with advances in statistical computing, makes it possible to apply these emerging statistical methods in in vitro and in vivo drug combination assessments. However, despite these advances, no book has served as a single source of information for statistical methods in drug combination research, nor has there been any guidance for experimental strategies.

Bayesian modeling has become an indispensable tool for ecological research because it is uniquely suited to deal with complexity in a statistically coherent way. This textbook provides a comprehensive and accessible introduction to the latest Bayesian methods--in language ecologists can understand. Unlike other books on the subject, this one emphasizes the principles behind the computations, giving ecologists a big-picture understanding of how to implement this powerful statistical approach.

Bayesian Models is an essential primer for non-statisticians. It begins with a...