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- Bayesian Inference

- Author : Hanns L. Harney
- Publsiher : Springer Science & Business Media
- Release : 20 May 2003
- ISBN : 9783540003977
- Pages : 263 pages
- Rating : 4/5 from 21 reviews

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Read or download book entitled Bayesian Inference written by Hanns L. Harney which was release on 20 May 2003, this book published by Springer Science & Business Media. Available in PDF, EPUB and Kindle Format. Book excerpt: Solving a longstanding problem in the physical sciences, this text and reference generalizes Gaussian error intervals to situations in which the data follow distributions other than Gaussian. The text is written at introductory level, with many examples and exercises.

- Author : Hanns L. Harney
- Publisher : Springer Science & Business Media
- Release Date : 2003-05-20
- Total pages : 263
- ISBN : 9783540003977

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**Summary :** Solving a longstanding problem in the physical sciences, this text and reference generalizes Gaussian error intervals to situations in which the data follow distributions other than Gaussian. The text is written at introductory level, with many examples and exercises....

- Author : David C. Knill,Whitman Richards
- Publisher : Cambridge University Press
- Release Date : 1996-09-13
- Total pages : 516
- ISBN : 9783540003977

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**Summary :** This 1996 book describes an exciting theoretical paradigm for visual perception based on experimental and computational insights....

- Author : Javier Prieto Tejedor
- Publisher : BoD – Books on Demand
- Release Date : 2017-11-02
- Total pages : 378
- ISBN : 9783540003977

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**Summary :** The range of Bayesian inference algorithms and their different applications has been greatly expanded since the first implementation of a Kalman filter by Stanley F. Schmidt for the Apollo program. Extended Kalman filters or particle filters are just some examples of these algorithms that have been extensively applied to logistics, ...

- Author : Hanns Ludwig Harney
- Publisher : Springer
- Release Date : 2016-10-18
- Total pages : 243
- ISBN : 9783540003977

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**Summary :** This new edition offers a comprehensive introduction to the analysis of data using Bayes rule. It generalizes Gaussian error intervals to situations in which the data follow distributions other than Gaussian. This is particularly useful when the observed parameter is barely above the background or the histogram of multiparametric data ...

- Author : Leonhard Held,Daniel Sabanés Bové
- Publisher : Springer Nature
- Release Date : 2020-03-31
- Total pages : 402
- ISBN : 9783540003977

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**Summary :** This richly illustrated textbook covers modern statistical methods with applications in medicine, epidemiology and biology. Firstly, it discusses the importance of statistical models in applied quantitative research and the central role of the likelihood function, describing likelihood-based inference from a frequentist viewpoint, and exploring the properties of the maximum likelihood ...

- Author : Lyle D. Broemeling
- Publisher : CRC Press
- Release Date : 2017-12-12
- Total pages : 432
- ISBN : 9783540003977

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**Summary :** This is the first book designed to introduce Bayesian inference procedures for stochastic processes. There are clear advantages to the Bayesian approach (including the optimal use of prior information). Initially, the book begins with a brief review of Bayesian inference and uses many examples relevant to the analysis of stochastic ...

- Author : Luc Bauwens,Michel Lubrano,Jean-François Richard
- Publisher : OUP Oxford
- Release Date : 2000-01-06
- Total pages : 366
- ISBN : 9783540003977

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**Summary :** This book contains an up-to-date coverage of the last twenty years advances in Bayesian inference in econometrics, with an emphasis on dynamic models. It shows how to treat Bayesian inference in non linear models, by integrating the useful developments of numerical integration techniques based on simulations (such as Markov Chain ...

- Author : Coryn A. L. Bailer-Jones
- Publisher : Cambridge University Press
- Release Date : 2017-04-27
- Total pages : 212
- ISBN : 9783540003977

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**Summary :** Science is fundamentally about learning from data, and doing so in the presence of uncertainty. This volume is an introduction to the major concepts of probability and statistics, and the computational tools for analysing and interpreting data. It describes the Bayesian approach, and explains how this can be used to ...

- Author : George E. P. Box,George C. Tiao
- Publisher : John Wiley & Sons
- Release Date : 2011-01-25
- Total pages : 608
- ISBN : 9783540003977

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**Summary :** Its main objective is to examine the application and relevance of Bayes' theorem to problems that arise in scientific investigation in which inferences must be made regarding parameter values about which little is known a priori. Begins with a discussion of some important general aspects of the Bayesian approach such ...

- Author : Mohammad Saber Fallah Nezhad
- Publisher : BoD – Books on Demand
- Release Date : 2014-04-29
- Total pages : 166
- ISBN : 9783540003977

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**Summary :** Dynamic programming and Bayesian inference have been both intensively and extensively developed during recent years. Because of these developments, interest in dynamic programming and Bayesian inference and their applications has greatly increased at all mathematical levels. The purpose of this book is to provide some applications of Bayesian optimization and ...

- Author : Nick Heard
- Publisher : Springer Nature
- Release Date : 2021-10-17
- Total pages : 177
- ISBN : 9783540003977

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**Summary :** These lecture notes provide a rapid, accessible introduction to Bayesian statistical methods. The course covers the fundamental philosophy and principles of Bayesian inference, including the reasoning behind the prior/likelihood model construction synonymous with Bayesian methods, through to advanced topics such as nonparametrics, Gaussian processes and latent factor models. These ...

- Author : Frederic Dambreville
- Publisher : Infinite Study
- Release Date : 2022-09-25
- Total pages : 38
- ISBN : 9783540003977

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**Summary :** This work proposes a logical interpretation of the non hybrid Dezert Smarandache Theory (DSmT). As probability is deeply related to a classical semantic, it appears that DSmT relies on an alternative semantic of decision. This semantic is characterized as a probabilized multi-modal logic....

- Author : Rainer Fischer,Roland Preuss,Udo von Toussaint
- Publisher : A I P Press
- Release Date : 2004-11-19
- Total pages : 605
- ISBN : 9783540003977

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**Summary :** All papers were peer reviewed. Bayesian Inference and Maximum Entropy Methods in Science and Engineering provide a framework for analyzing ill-conditioned data. Maximum Entropy is a theoretical method to draw conclusions when little information is available. Bayesian probability theory provides a formalism for scientific reasoning by analyzing noisy or imcomplete ...

- Author : Herbert Hoijtink,Irene Klugkist,Paul Boelen
- Publisher : Springer Science & Business Media
- Release Date : 2008-09-08
- Total pages : 361
- ISBN : 9783540003977

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**Summary :** This book provides an overview of the developments in the area of Bayesian evaluation of informative hypotheses that took place since the publication of the ?rst paper on this topic in 2001 [Hoijtink, H. Con?rmatory latent class analysis, model selection using Bayes factors and (pseudo) likelihood ratio statistics. Multivariate Behavioral ...

- Author : Stephen W. Raudenbush,Anthony S. Bryk
- Publisher : SAGE
- Release Date : 2002
- Total pages : 520
- ISBN : 9783540003977

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**Summary :** New edition of a text in which Raudenbush (U. of Michigan) and Bryk (sociology, U. of Chicago) provide examples, explanations, and illustrations of the theory and use of hierarchical linear models (HLM). New material in Part I (Logic) includes information on multivariate growth models and other topics....