Bayesian – alle Bücher, Blu-ray Discs und CDs

N Thompson Hobbs, Mevin B Hooten

Bayesian Models

A fully updated and expanded edition of the essential primer on Bayesian modeling for ecologists Uniquely suited to deal with complexity in a statistically coherent way, Bayesian modeling has become an i…

Erkki Somersalo, Daniela Calvetti

Bayesian Scientific Computing

The once esoteric idea of embedding scientific computing into a probabilistic framework, mostly along the lines of the Bayesian paradigm, has recently enjoyed wide popularity and found its way into numero…

Nonparametric Bayesian Inference

This book is a compilation of unpublished papers written by Jean-Marie Rolin (with several co-authors) on nonparametric bayesian estimation. Jean-Marie was professor of statistics at University of Louvain…

Peter E Rossi, Greg M Allenby, Sanjog Misra

Bayesian Statistics and Marketing

Fine-tune your marketing research with this cutting-edge statistical toolkit Bayesian Statistics and Marketing illustrates the potential for applying a Bayesian approach to some of the most challenging an…

Bayesian Network Modeling of Corrosion

This book represents a compilation of experience from a slate of experts involved in developing and deploying Bayesian Networks (BN) for corrosion management. The contributors describe how probability dis…

Kazuho Watanabe, Masashi Sugiyama, Shinichi Nakajima

Variational Bayesian Learning Theory

This introduction to the theory of variational Bayesian learning summarizes recent developments and suggests practical applications.

Jeff Gill, Le Bao

Bayesian Social Science Statistics

This Element is an introduction to Bayesian statistics for social science students and practitioners starting from the absolute beginning.

Michael Rescorla

Bayesian Models of the Mind

Bayesian decision theory is a mathematical framework used by cognitive scientists to model reasoning and decision-making under uncertain conditions. It has been used to describe the human mind, revealing …

Michael Rescorla

Bayesian Models of the Mind

Bayesian decision theory is a mathematical framework used by cognitive scientists to model reasoning and decision-making under uncertain conditions. It has been used to describe the human mind, revealing …

New Frontiers in Bayesian Statistics

This book presents a selection of peer-reviewed contributions to the fifth Bayesian Young Statisticians Meeting, BaYSM 2021, held virtually due to the COVID-19 pandemic on 1-3 September 2021. Despite all …

Qing Zhao

Bayesian Analysis of Spatially Structured Population Dynamics

The book introduces a series of state-of-art Bayesian models that can be used to understand and predict spatially structured population dynamics in our changing world. Several chapters are devoted to intr…

Statistical Modeling Using Bayesian Latent Gaussian Models

This book focuses on the statistical modeling of geophysical and environmental data using Bayesian latent Gaussian models. The structure of these models is described in a thorough introductory chapter, wh…

Rose T. Faghih, Dilranjan S. Wickramasuriya

Bayesian Filter Design for Computational Medicine

This book serves as a tutorial that explains how different state estimators (Bayesian filters) can be built when all or part of the observations are binary. The book begins by briefly motivating the need …

Bayesian Statistics, New Generations New Approaches

This book hosts the results presented at the 6th Bayesian Young Statisticians Meeting 2022 in Montréal, Canada, held on June 22 23, titled "Bayesian Statistics, New Generations New Approaches". This colle…

Lawrence D. Stone, Stephen L. Anderson, Roy L. Streit

Introduction to Bayesian Tracking and Particle Filters

This book provides a quick but insightful introduction to Bayesian tracking and particle filtering for a person who has some background in probability and statistics and wishes to learn the basics of sing…

Henning Omre, Ole Bernhard Forberg, Torstein M. Fjeldstad

Bayesian Spatial Modelling with Conjugate Prior Models

This book offers a comprehensive overview of statistical methodology for modelling and evaluating spatial variables useful in a variety of applications. These spatial variables fall into three categories:…

Hans Söllner

Bayerman Vibration

Lei Cheng, Yik-Chung Wu, Zhongtao Chen

Bayesian Tensor Decomposition for Signal Processing and Machine Learning

This book presents recent advances of Bayesian inference in structured tensor decompositions. It explains how Bayesian modeling and inference lead to tuning-free tensor decomposition algorithms, which ach…

Tom Chivers

Everything Is Predictable

"At its simplest, Bayes's theorem describes the probability of an event, based on prior knowledge of conditions that might be related to the event. But in [this book], Tom Chivers lays out how it affects …