Bayesian inference

These lecture notes provide a rapid, accessible introduction to Bayesian statistical methods.

This volume brings together the main results in the field of Bayesian Optimization (BO), focusing on the last ten years and showing how, on the basic framework, new methods have been specialized to solve emerging problems from machine learning, artificial intelligence, and system optimization.

A comprehensive resource that offers an introduction to statistics with a Bayesian angle, for students of professional disciplines like engineering and economics The Bayesian Way offers a basic introduction to statistics that emphasizes the Bayesian approach and is designed for use by those studying professional disciplines like engineering and economics.

This book provides a coherent framework for understanding shrinkage estimation in statistics.

This book introduces readers to Bayesian optimization, highlighting advances in the field and showcasing its successful applications to computer experiments.

This book deals with selected problems of machine perception, using various 2D and 3D imaging sensors.

Bayesian Networks This book should have a place on the bookshelf of every forensic scientist who cares about the science of evidence interpretation.

The volume includes a collection of peer-reviewed contributions from among those presented at the main conference organized yearly by the Mexican Statistical Association (AME) and every two years by a Latin-American Confederation of Statistical Societies.

This book provides an extensive coverage of the methodology of survival analysis, ranging from introductory level material to deeper more advanced topics.

Make your own luck by understanding probability Over the years, some very smart people have thought they understood the rules of chance?

Bayesian statistics is currently undergoing something of a renaissance.

Highlights the advantages of using the tripartite model within a Bayesian framework for estimation of time calibrated phylogenetic trees.

If you know how to program, you're ready to tackle Bayesian statistics.

This book walks you through learning probability and statistics from a Bayesian point of view.

This book provides, as simply as possible, sound foundations for an in-depth understanding of reliability engineering with regard to qualitative analysis, modelling, and probabilistic calculations of safety and production systems.

A comprehensive resource that draws a balance between theory and applications of nonlinear time series analysis Nonlinear Time Series Analysis offers an important guide to both parametric and nonparametric methods, nonlinear state-space models, and Bayesian as well as classical approaches to nonlinear time series analysis.

Probabilistic Finite Element Model Updating Using Bayesian Statistics: Applications to Aeronautical and Mechanical Engineering Tshilidzi Marwala and Ilyes Boulkaibet, University of Johannesburg, South Africa Sondipon Adhikari, Swansea University, UK Covers the probabilistic finite element model based on Bayesian statistics with applications to aeronautical and mechanical engineering Finite element models are used widely to model the dynamic behaviour of many systems including in electrical, aerospace and mechanical engineering.

This book introduces the major concepts of probability and statistics, along with the necessary computational tools, for undergraduates and graduate students.

This book provides an accessible approach to Bayesian computing and data analysis, with an emphasis on the interpretation of real data sets.

The Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability represents a monumental effort in advancing the discourse on probability theory and statistical applications across a wide range of scientific disciplines.

Many people find statistics confusing, and perhaps even more confusing given recent publicity about problems with traditional p-values and alternative statistical techniques including confidence intervals and Bayesian statistics.

An Introduction to Stochastic Modeling, Student Solutions Manual (e-only)

This book focuses on the structural analysis of demand under block rate pricing, a type of nonlinear pricing used mainly in public utility services.

This book presents a wide range of topics to address the needs of several groups of users of rapidly growing methods of generalized linear models.

This book explains the misuses and abuses of Null Hypothesis Significance Tests, which are reconsidered in light of Jeffreys' Bayesian concept of the role of statistical inference, in experimental investigations.

This book is a rigorous but practical presentation of the Bayesian techniques of uncertainty quantification, with applications in R.

This book offers a comprehensive reference guide to neutrosophic theory and its applications in decision-making in numerous disciplines, ranging from business, economics and management, computer science, health and environmental sciences, and many others.

This volume on the latest developments in statistical modelling is a collection of refereed papers presented at the 38th International Workshop on Statistical Modelling, IWSM 2024, held from 14 to 19 July 2024 in Durham, UK.

This book explains the importance of using the probability that the hypothesis is correct (PHC), an intuitive measure that anyone can understand, as an alternative to the p-value.

This book offers a comprehensive overview of statistical methodology for modelling and evaluating spatial variables useful in a variety of applications.

This book provides a comprehensive introduction to statistical approaches for the assessment of complex environmental exposures, such as pollutants and chemical mixtures, within the exposome framework.

This book explains the importance of using the probability that the hypothesis is correct (PHC), an intuitive measure that anyone can understand, as an alternative to the p-value.

This graduate textbook on the statistical approach to data science describes the basic ideas, scientific principles and common techniques for the extraction of mathematical models from observed data.

This book introduces some recent developments in Bayesian real-time system identification.

This book examines statistical models for frequency data.

This book provides a self-contained introduction of Stein/shrinkage estimation for the mean vector of a multivariate normal distribution.

This book provides a self-contained introduction of mixed-effects models and small area estimation techniques.

This volume on the latest developments in statistical modelling is a collection of refereed papers presented at the 38th International Workshop on Statistical Modelling, IWSM 2024, held from 14 to 19 July 2024 in Durham, UK.

This book explains the misuses and abuses of Null Hypothesis Significance Tests, which are reconsidered in light of Jeffreys' Bayesian concept of the role of statistical inference, in experimental investigations.

This book provides a comprehensive introduction to statistical approaches for the assessment of complex environmental exposures, such as pollutants and chemical mixtures, within the exposome framework.

This book examines statistical models for frequency data.

This richly illustrated textbook covers modern statistical methods with applications in medicine, epidemiology and biology.

This book is a compilation of unpublished papers written by Jean-Marie Rolin (with several co-authors) on nonparametric bayesian estimation.

This book introduces some recent developments in Bayesian real-time system identification.

This book provides a self-contained introduction of Stein/shrinkage estimation for the mean vector of a multivariate normal distribution.

This book focuses on the structural analysis of demand under block rate pricing, a type of nonlinear pricing used mainly in public utility services.

This book offers a comprehensive reference guide to neutrosophic theory and its applications in decision-making in numerous disciplines, ranging from business, economics and management, computer science, health and environmental sciences, and many others.