Introduction to Imprecise Probabilities Introduction to Imprecise Probabilities
Wiley Series in Probability and Statistics

Introduction to Imprecise Probabilities

Thomas Augustin và các tác giả khác
    • 104,99 US$
    • 104,99 US$

Lời Giới Thiệu Của Nhà Xuất Bản

In recent years, the theory has become widely accepted and has been further developed, but a detailed introduction is needed in order to make the material available and accessible to a wide audience. This will be the first book providing such an introduction, covering core theory and recent developments which can be applied to many application areas. All authors of individual chapters are leading researchers on the specific topics, assuring high quality and up-to-date contents.
An Introduction to Imprecise Probabilities provides a comprehensive introduction to imprecise probabilities, including theory and applications reflecting the current state if the art. Each chapter is written by experts on the respective topics, including: Sets of desirable gambles; Coherent lower (conditional) previsions; Special cases and links to literature; Decision making; Graphical models; Classification; Reliability and risk assessment; Statistical inference; Structural judgments; Aspects of implementation (including elicitation and computation); Models in finance; Game-theoretic probability; Stochastic processes (including Markov chains); Engineering applications.

Essential reading for researchers in academia, research institutes and other organizations, as well as practitioners engaged in areas such as risk analysis and engineering.

THỂ LOẠI
Khoa Học & Tự Nhiên
ĐÃ PHÁT HÀNH
2014
11 tháng 4
NGÔN NGỮ
EN
Tiếng Anh
ĐỘ DÀI
448
Trang
NHÀ XUẤT BẢN
Wiley
NGƯỜI BÁN
John Wiley & Sons, Inc.
KÍCH THƯỚC
47,8
Mb
Uncertainty and Risk Uncertainty and Risk
2007
Decision Processes by Using Bivariate Normal Quantile Pairs Decision Processes by Using Bivariate Normal Quantile Pairs
2015
Foundations of Info-Metrics Foundations of Info-Metrics
2017
Probability Theory and Statistical Inference Probability Theory and Statistical Inference
2019
Case-Based Approximate Reasoning Case-Based Approximate Reasoning
2007
Foundations of Computational Intelligence Volume 5 Foundations of Computational Intelligence Volume 5
2008
Pricing Insurance Risk Pricing Insurance Risk
2022
Applied Logistic Regression Applied Logistic Regression
2013
Machine Learning Machine Learning
2018
Introduction to Linear Regression Analysis Introduction to Linear Regression Analysis
2021
Categorical Data Analysis Categorical Data Analysis
2013
Statistical Rules of Thumb Statistical Rules of Thumb
2011