Gaussian Markov Random Fields - Info and Reading Options
Theory and Applications (Monographs on Statistics and Applied Probability)
By Havard Rue and Leonhard Held
"Gaussian Markov Random Fields" is published by Chapman & Hall/CRC in February 18, 2005, it has 263 pages and the language of the book is English.
“Gaussian Markov Random Fields” Metadata:
- Title: Gaussian Markov Random Fields
- Authors: Havard RueLeonhard Held
- Language: English
- Number of Pages: 263
- Publisher: Chapman & Hall/CRC
- Publish Date: February 18, 2005
“Gaussian Markov Random Fields” Subjects and Themes:
- Subjects: ➤ Gaussian Markov random fields - Gauge fields (physics) - Nomesh - MATHEMATICS - Probability & Statistics - Stochastic Processes - Stochastischer Prozess - Gauß-Zufallsfeld - Markov-Feld - Campos aleatórios markovianos - Probabilidade - Statistics as Topic - Statistical Models - Markov Chains - Markov-Zufallsfeld
Edition Specifications:
- Format: Hardcover
- Weight: 1 pounds
- Dimensions: 8.9 x 6.2 x 0.8 inches
Edition Identifiers:
- The Open Library ID: OL8795399M - OL19852215W
- Online Computer Library Center (OCLC) ID: 123439153 - 57068944
- Library of Congress Control Number (LCCN): 2004061870
- ISBN-13: 9781584884323
- ISBN-10: 1584884320
- All ISBNs: 1584884320 - 9781584884323
AI-generated Review of “Gaussian Markov Random Fields”:
Snippets and Summary:
This monograph considers Gaussian Markov random fields (GMRFs) covering both theory and applications.
"Gaussian Markov Random Fields" Description:
The Open Library:
"Gaussian Markov Random Fields: Theory and Applications provides a reference, using a unified framework for representing and understanding GMRFs. Various case studies illustrate the use of GMRFs in complex hierarchical models, in which statistical inference is only possible using Markov Chain Monte Carlo (MCMC) techniques. The authors, preeminent experts in the field, emphasize the computational aspects, construct fast and reliable algorithms for MCMC inference, and provide an online C-library for fast and exact simulation.". "This is an ideal tool for researchers and students in statistics, particularly biostatistics and spatial statistics, as well as quantitative researchers in engineering, epidemiology, image analysis, geography, and ecology, introducing them to this powerful statistical inference method."--BOOK JACKET.
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