Gaussian Markov Random Fields: Theory and Applications by Havard Rue, Leonhard Held

Gaussian Markov Random Fields: Theory and Applications Havard Rue, Leonhard Held ebook
Page: 259
Publisher: Chapman and Hall/CRC
ISBN: 1584884320, 9781584884323
Format: djvu

Jul 5, 2008 - One of the most exciting recent developments in stochastic simulation is perfect (or exact) simulation, which turns out to be particularly applicable for most point process models and many Markov random field models as demonstrated in my work. Of the problem and the design of the data-gathering activity}"). Recently, in connection to Published in 2004 by Chapman and Hall/CRC, it provides a detailed account on the theory of spatial point process models and simulation-based inference as well as various application examples. Aug 9, 2011 - Markov random fields and graphical models are widely used to represent conditional independences in a given multivariate probability distribution (see [1–5], to name just a few). Aug 10, 2010 - His main research interests are computational methods for Bayesian inference, spatial modelling, Gaussian Markov random fields and stochastic partial differential equations, with applications in geostatistics and climate modelling. The spatially uncorrelated effects are assumed to be i.i.d. He is among the developers of the statistical software INLA . Aug 11, 2011 - For the spatially correlated effect, Markov random field prior is chosen. Rue H, Held L: Gaussian Markov Random Fields: Theory and Applications. Successfully developing such a logical progression would yield a Theory of Applied Statistics, which we need and do not yet have. Oct 1, 2010 - Gaussian Markov Random Fields: Theory and Applications. تعداد صفحات: ۲۵۹ ||| حجم فایل: ۲.۲۵ MB ||| زبان : انگلیسی. Jan 19, 2012 - Gaussian markov random fields.