For over 30 years, the MaxEnt workshops have explored Bayesian and Maximum Entropymethods in scientific, engineering, and signal processing applications. This proceedings volume covers all aspects of
MaxEnt workshops are devoted to Bayesian inference and Maximum Entropy methods in sciences and engineering. This year's meeting was also encompassed all aspects of probabilistic inference such as foun
The MaxEnt2008 - 28th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering - encompassed all aspects of information theory, probability, statistical infe
This excellent volume considers the methods, applications and even the foundations of a key area of theoretical study. Namely, that of Bayesian probability, entropy and information theory in scientifi
Like all previous MaxEnt Workshops, this meeting encompassed all aspects of probabilistic inference including foundations, computational methods, and applications. The topics represented included prob
Papers from an August 2002 workshop reflect recent research on statistical inference, signal separation, physics applications, and inductive logic theory. Some specific topics include Chernoff's bound
Bayesian Inference for Probabilistic Risk Assessment provides a Bayesian foundation for framing probabilistic problems and performing inference on these problems. Inference in the book employs a moder
?This monograph provides the fundamentals of statistical inference for financial engineering and covers some selected methods suitable for analyzing financial time series data. In order to describe th
Bayesian methods are growing more and more popular, finding new practical applications in the fields of health sciences, engineering, environmental sciences, business and economics and social sciences
This new edition has been completely revised to reflect the notable innovations in mining engineering and the remarkable developments in the science of rock mechanics and the practice of rock angineer
As chapters in this book demonstrate, BNP has important uses in clinical sciences and inference for issues like unknown partitions in genomics. Nonparametric Bayesian approaches (BNP) play an ever exp
This book explores advanced Bayesian statistical methods for extracting key information for cosmological model selection, parameter inference and forecasting from astrophysical observations, in partic
These are the proceedings of the 20th international conference on domain decomposition methods in science and engineering. Domain decomposition methods are iterative methods for solving the often very
Forty years ago, in 1957, the Principle of Maximum Entropy was first intro- duced by Jaynes into the field of statistical mechanics. Since that seminal publication, this principle has been adopted in
These are the proceedings of the 19th international conference on domain decomposition methods in science and engineering. Domain decomposition methods are iterative methods for solving the often very
These are the proceedings of the 18th international conference on domain decomposition methods in science and engineering, held?in Jerusalem, January 12-17, 2008. Domain decomposition methods are iter
Bayesian Reliability presents modern methods and techniques for analyzing reliability data from a Bayesian perspective. The adoption and application of Bayesian methods in virtually all branches of sc
Bayesian inference networks, a synthesis of statistics and expert systems, have advanced reasoning under uncertainty in medicine, business, and social sciences. This innovative volume is the first com
This volume contains a selection of papers presented at the 21st international conference on domain decomposition methods in science and engineering held in Rennes, France, June 25-29, 2012. Domain de
This book covers statistical inference based on the likelihood function. Discusses frequentist likelihood-based inference from a Fisherian viewpoint, Bayesian inference techniques including point and
This text is concerned with Bayesian learning, inference and forecasting in dynamic environments. We describe the structure and theory of classes of dynamic models and their uses in forecasting and ti
?This book is for students and researchers who have had a first year graduate level mathematical statistics course. It covers classical likelihood, Bayesian, and permutation inference; an introductio
This book provides a balanced, modern introduction to Bayesian and frequentist methods for regression analysis. The author discusses Frequentist and Bayesian Inferences; Linear Models; Binary Data Mod
The two volumes contain 65 chapters, which are based on talks presented by reputable researchers in the field at the Tenth International Conference on Integral Methods in Science and Engineering. The
In this book, we provide an easy introduction to Bayesian inference using MCMC techniques, making most topics intuitively reasonable and deriving to appendixes the more complicated matters. The biolog
The fundamentals of methods in nuclear geophysics and their practical applications in engineering geology, hydrology, hydrogeology, agriculture and environmental science are discussed in this book. Th
This textbook covers the fundamentals of statistical inference and statistical theory including Bayesian and frequentist approaches and methodology possible without excessive emphasis on the underlyin
This book, suitable for numerate biologists and for applied statisticians, provides the foundations of likelihood, Bayesian and MCMC methods in the context of genetic analysis of quantitative traits.
This book explains the foundation of approximate Bayesian computation (ABC), an approach to Bayesian inference that does not require the specification of a likelihood function. As a result, ABC can be
This volume contains the post-proceedings of the 9th Doctoral Workshop on Mathematical and Engineering Methods in Computer Science, MEMICS 2014, held in Telc, Czech Republic, in October 2014.The 13 th
Yeast Metabolic Engineering: Methods and Protocols provides the widely established basic tools used in yeast metabolic engineering, while describing in deeper detail novel and innovative methods that
Distributions in the Physical and Engineering Sciences is a comprehensive exposition on analytic methods for solving science and engineering problems which is written from the unifying viewpoint of di
Fundamentals of Matrix-Analytic Methods targets advanced-level students in mathematics, engineering and computer science. It focuses on the fundamental parts of Matrix-Analytic Methods, Phase-Type Dis
This volume contains the post-proceedings of the 8th Doctoral Workshop on Mathematical and Engineering Methods in Computer Science, MEMICS 2012, held in Znojmo, Czech Republic, in October, 2012.The 13
This volume constitutes the thoroughly refereed post-conference proceedings of the 7th International Doctoral Workshop on Mathematical and Engineering Methods in Computer Science, MEMICS 2011, held in
This book provides the foundations of likelihood, Bayesian and MCMC methods in the context of genetic analysis of quantitative traits. Considerably more detail is offered than what may be warranted f
Survival analysis arises in many fields of study including medicine, biology, engineering, public health, epidemiology, and economics. This book provides a comprehensive treatment of Bayesian survival
Survival analysis arises in many fields of study including medicine, biology, engineering, public health, epidemiology, and economics. This book provides a comprehensive treatment of Bayesian survival
This first edition focuses on probability and the Bayesian viewpoint. It presents basic material on probability and then introduces inference by means of Bayes' rule. The emphasis is on statistical th
This book, now in its second edition, provides a comprehensive overview of current re-irradiation strategies, with detailed discussion of re-irradiation methods, technical aspects, the role of combine
