JSTOR Daily

BAYESIAN NONHOMOGENEOUS MARKOV MODELS VIA PÓLYA-GAMMA DATA AUGMENTATION WITH APPLICATIONS TO RAINFALL MODELING

Discrete-time hidden Markov models are a broadly useful class of latent variable models with applications in areas such as speech recognition, bioinformatics, and climate data analysis. It is common ...
Nature

Markov Chains and Hidden Markov Models

Markov chains provide a fundamental framework for modelling stochastic processes, where the next state depends solely on the current state. Hidden Markov models (HMMs) extend this framework by ...
JSTOR Daily

A BAYESIAN HIERARCHICAL SPATIAL MODEL FOR DENTAL CARIES ASSESSMENT USING NON-GAUSSIAN MARKOV RANDOM FIELDS

This is a preview. Log in through your library . Abstract Research in dental caries generates data with two levels of hierarchy: that of a tooth overall and that of the different surfaces of the tooth ...
Forbes

Revealing Secrets Of Large Language Models And Generative AI Via Markov Chain Mathematics

Forbes contributors publish independent expert analyses and insights. Dr. Lance B. Eliot is a world-renowned AI scientist and consultant. In today’s column, I closely examine an innovative way of ...
Insurancenewsnet.com

New Information Technology Findings from University of Iceland Discussed (Calibration of Ground Motion Models To Icelandic Peak Ground Acceleration Data Using Bayesian Markov ...

2019 JUN 12 (NewsRx) -- By a News Reporter-Staff News Editor at Information Technology Daily-- Data detailed on Information Technology have been presented. According to news originating from Reykjavik ...
University of Bristol

Markov disease progression models

Markov Models for disease progression are common in medical decision making (see references below). The parameters in a Markov model can be estimated by observing the time it takes patients in any ...