Results 21 to 30 of about 102,383 (223)

Parsing social network survey data from hidden populations using stochastic context-free grammars. [PDF]

PLoS ONE, 2009
BACKGROUND:Human populations are structured by social networks, in which individuals tend to form relationships based on shared attributes. Certain attributes that are ambiguous, stigmatized or illegal can create a OhiddenO population, so-called because ...
Art F Y Poon, Kimberly C Brouwer, Steffanie A Strathdee, Michelle Firestone-Cruz, Remedios M Lozada, Sergei L Kosakovsky Pond, Douglas D Heckathorn, Simon D W Frost   +7 more
doaj   +1 more source

Unsupervised statistical image segmentation using bi-dimensional hidden Markov chains model with application to mammography images

Journal of King Saud University: Computer and Information Sciences, 2023
Hidden Markov chain (HMC) models have been widely used in unsupervised image segmentation. In these models, there is a double process; a hidden one noted X and an observed one, which is often one-dimensional, noted Y.
Abdelali Joumad, Abdelmajid El Moutaouakkil, Abdelaziz Nasroallah, Omar Boutkhoum, Furqan Rustam, Imran Ashraf   +5 more
doaj   +1 more source

Convergence in distribution for filtering processes associated to Hidden Markov Models with densities

, 2013
Consider a filtering process associated to a hidden Markov model with densities for which both the state space and the observation space are complete, separable, metric spaces.
Kaijser, Thomas
core   +1 more source

Markov Chain Models for Stock Prices Forecasts and Analysis [PDF]

ITM Web of Conferences
Under the condition of complexity and volatility of financial markets, stock price prediction remains a challenging research topic. Markov chain models, with their “memoryless” nature, provide a probabilistic framework for analyzing stock price dynamics.
Jia Henghua
doaj   +1 more source

Derivatives of Entropy Rate in Special Families of Hidden Markov Chains [PDF]

, 2006
Consider a hidden Markov chain obtained as the observation process of an ordinary Markov chain corrupted by noise. Zuk, et. al. [13], [14] showed how, in principle, one can explicitly compute the derivatives of the entropy rate of at extreme values of ...
Author(s Han, Brian Marcus, G Marcus, Guangyue Han   +3 more
core   +2 more sources

Markov Chain Computation for Homogeneous and Non-homogeneous Data: MARCH 1.1 Users Guide

Journal of Statistical Software, 2001
MARCH is a free software for the computation of different types of Markovian models including homogeneous Markov Chains, Hidden Markov Models (HMMs) and Double Chain Markov Models (DCMMs). The main characteristic of this software is the implementation of
Andre Berchtold
doaj   +1 more source

A Hidden Markov Model to Address Measurement Errors in Ordinal Response Scale and Non-Decreasing Process

Mathematics, 2020
A Bayesian approach was developed, tested, and applied to model ordinal response data in monotone non-decreasing processes with measurement errors. An inhomogeneous hidden Markov model with continuous state-space was considered to incorporate measurement
Lizbeth Naranjo, Luz Judith R. Esparza, Carlos J. Pérez   +2 more
doaj   +1 more source

On Geometric Ergodicity of Skewed - SVCHARME models

, 2012
Markov Chain Monte Carlo is repeatedly used to analyze the properties of intractable distributions in a convenient way. In this paper we derive conditions for geometric ergodicity of a general class of nonparametric stochastic volatility models with ...
Asai, Bhattacharia, Bhattacharia, Caporin, Cappuccio, Danielsson, Danielsson, Geweke, Glosten, Hansen, Harvey, Harvey, Harvey, Hull, Jacquier, Jerzy P. Rydlewski, Kalimipalli, Lee, Małgorzata Snarska, McAleer, Meyn, Nelson, Rohan, Selçuk, Shephard, Shephard, So, Stockis, Taylor, Tsiotas, Wang, Wiggins   +31 more
core   +1 more source

Markov Observation Models and Deepfakes

Mathematics
Herein, expanded Hidden Markov Models (HMMs) are considered as potential deepfake generation and detection tools. The most specific model is the HMM, while the most general is the pairwise Markov chain (PMC). In between, the Markov observation model (MOM)
Michael A. Kouritzin
doaj   +1 more source

General limit distributions for sums of random variables with a matrix product representation

, 2014
The general limit distributions of the sum of random variables described by a finite matrix product ansatz are characterized. Using a mapping to a Hidden Markov Chain formalism, non-standard limit distributions are obtained, and related to a form of ...
Abry, Patrice, Angeletti, Florian, Bertin, Eric   +2 more
core   +1 more source