ABSTRACT: In this work, we study some computational aspects for the Bayesian analysis involving stable distributions. It is well known that, in general, there is no closed form for the probability ...

A demonstration of the Metropolis-Hastings MCMC algorithm that infers the parameters of a 3D line from noisy 2D images.

ABSTRACT: This paper proposes a Full Range Gaussian Markov Random Field (FRGMRF) model for monochrome image compression, where images are assumed to be Gaussian Markov Random Field. The parameters of ...

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The efficient resolution of optimization problems is one of the key issues in today’s industry. This task relies mainly on classical algorithms that present scalability problems and processing ...

Abstract: This paper presents a new method to synthesize safe reversible Markov chains via classical Metropolis-Hastings (M-H) algorithm. Classical M-H algorithm does not impose safety constraints on ...

Department of Counseling, Quantitative Methods, and Special Education, Southern Illinois University Carbondale, Carbondale, IL, USA This study compared several parameter estimation methods for ...