Results 271 to 280 of about 440,340 (303)
Some of the next articles are maybe not open access.
1992
Abstract In Section 7.3, we briefly introduced models for Markov chains in the simple case where there were only two possible responses: an event occurs or not. However, such models have much wider application. In continuous time models, where each subject is in one of several possible states at any given point, they are often called ...
openaire +1 more source
Abstract In Section 7.3, we briefly introduced models for Markov chains in the simple case where there were only two possible responses: an event occurs or not. However, such models have much wider application. In continuous time models, where each subject is in one of several possible states at any given point, they are often called ...
openaire +1 more source
1990
Markovian processes (semi-Markov and Markov) are processes included in a wider class of processes where one has an explicit time dependence (the dynamic aspect) as well as the stochastic character of the states evolution (therefore probabilistic). They are part of dynamic probabilistic systems.
openaire +1 more source
Markovian processes (semi-Markov and Markov) are processes included in a wider class of processes where one has an explicit time dependence (the dynamic aspect) as well as the stochastic character of the states evolution (therefore probabilistic). They are part of dynamic probabilistic systems.
openaire +1 more source
Strong Markov Properties for Markov Random Fields
Journal of Theoretical Probability, 2000Markov properties for random fields are established. The author presents a multidimensional extension of stopping times by introducing random membranes. A special case of the random membrane is considered to obtain strong Markov property for a point process under Evstigneev's nonanticipating sufficient conditions.
openaire +2 more sources
Markov blanket and Markov boundary of multiple variables
J. Mach. Learn. Res., 2018Summary: Markov blanket (Mb) and Markov boundary (MB) are two key concepts in Bayesian networks (BNs). In this paper, we study the problem of Mb and MB for multiple variables. First, we show that Mb possesses the additivity property under the local intersection assumption, that is, an Mb of multiple targets can be constructed by simply taking the union
Xu-Qing Liu, Xin-sheng Liu
openaire +2 more sources
Markov properties of a Markov process
Zeitschrift f�r Wahrscheinlichkeitstheorie und Verwandte Gebiete, 1981Getoor, R. K., Sharpe, M. J.
openaire +1 more source
The Analysis of Panel Data under a Markov Assumption
Journal of the American Statistical Association, 1985J F Lawless, J D Kalbfleisch
exaly
An Introduction to Markov Modelling for Economic Evaluation
Pharmacoeconomics, 2012Andrew Briggs, Mark Sculpher
exaly
An introduction to hidden Markov models
IEEE ASSP Magazine (Acoustics, Speech, and Signal Processing), 1986L Rabiner
exaly