Finitary codings for spatial mixing Markov random fields

نویسندگان

چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Propp-Wilson Algorithms And Finitary Codings For High Noise Markov Random Fields

In this paper, we combine two previous works, the rst being by the rst author and K. Nelander, and the second by J. van den Berg and the second author, to show (1) that one can carry out a Propp{Wilson exact simulation for all Markov random elds on Z d satisfying a certain high noise assumption, and (2) that all such random elds are a nitary image of a nite state i.i.d. process. (2) is a streng...

متن کامل

Strong Spatial Mixing for Binary Markov Random Fields

The remarkable contribution by Weitz gives a general framework to establish the strong spatial mixing property of Gibbs measures. In light of Weitz’s work, we prove the strong spatial mixing for binary Markov random fields under the condition that the ‘external field’ is uniformly large or small by turning them into a corresponding Ising model. Our proof is done through a ‘path’ characterizatio...

متن کامل

Markov Random Fields and Conditional Random Fields

Markov chains provided us with a way to model 1D objects such as contours probabilistically, in a way that led to nice, tractable computations. We now consider 2D Markov models. These are more powerful, but not as easy to compute with. In addition we will consider two additional issues. First, we will consider adding observations to our models. These observations are conditioned on the value of...

متن کامل

Transformed Gaussian Markov Random Fields and 1 Spatial Modeling

15 The Gaussian random field (GRF) and the Gaussian Markov random field (GMRF) have 16 been widely used to accommodate spatial dependence under the generalized linear mixed 17 model framework. These models have limitations rooted in the symmetry and thin tail of the 18 Gaussian distribution. We introduce a new class of random fields, termed transformed GRF 19 (TGRF), and a new class of Markov r...

متن کامل

spMC: Modelling Spatial Random Fields with Continuous Lag Markov Chains

Abstract Currently, a part of the R statistical software is developed in order to deal with spatial models. More specifically, some available packages allow the user to analyse categorical spatial random patterns. However, only the spMC package considers a viewpoint based on transition probabilities between locations. Through the use of this package it is possible to analyse the spatial variabi...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: The Annals of Probability

سال: 2020

ISSN: 0091-1798

DOI: 10.1214/19-aop1405