Results 151 to 160 of about 8,159 (239)

Inferring Hidden Attentional States in Driving: A Bayesian Approach to Modeling Distraction and Secondary Task Engagement. [PDF]

Hum Factors
Dheeraj Kashyap L, Wang Z, Chang Y, Zahabi M, Garcia A.   +4 more
europepmc   +1 more source

hsmm -- An R package for analyzing hidden semi-Markov models

Hidden semi-Markov models are a generalization of the well-known hidden Markov model. They allow for a greater flexibility of sojourn time distributions, which implicitly follow a geometric distribution in the case of a hidden Markov chain.
Bulla, Jan, Bulla, Ingo, Nenadic, Oleg
core  

The occurrence of a particular state is a predictor of successful travel consultation. [PDF]

PLoS One
Honda H, Kubo T, Hisamatsu R, Ohmoto Y, Ikeda K, Ueda K.   +5 more
europepmc   +1 more source

A minimal chemo-mechanical Markov model for rotary catalysis of F₁-ATPase. [PDF]

Nat Commun
Chen Y, Grubmüller H.
europepmc   +1 more source

Unifying Repbase and Dfam: a new open foundation for transposable element research. [PDF]

Mob DNA
Kojima KK, Smit AFA, Bao W, Kohany O, Kojima NF, Jurka T, Hubley R, Wheeler TJ.   +7 more
europepmc   +1 more source

Determinants of stunting among under-five children in Amhara and Oromia regions, Ethiopia: the linear quantile regression analysis. [PDF]

BMC Public Health
Wachifo DD, Debeko DD, Asfaw ZG.
europepmc   +1 more source

Introduction to Hidden Semi-Markov Models

, 2018
John van der Hoek, Robert J. Elliott
openaire   +2 more sources

Combining EEG signals from the 2 members of a team to improve event identification. [PDF]

Neuroimage Rep
Fincham JM, Betts S, Anderson JR.
europepmc   +1 more source

Joint Bayesian Hidden Markov Model With Subject-Specific Transitions for Wearable Sensor Data. [PDF]

Stat Med
Fei W, Miao Z, Xu T, Wang Y.
europepmc   +1 more source

Multichain Hidden Markov and semi-Markov Models: Formalization, inference, and applications

Hidden Markov Models (HMMs) and Hidden Semi-Markov Models (HSMMs) are widely used statistical models for studying dynamic processes that cannot be observed directly or governed by a hidden layer. In many applications, particularly those involving spatial data, the hidden chain and the observed time series are multidimensional, exhibiting structured ...
Peyrard, Nathalie, Bacave, Hanna, Durand, Jean-Baptiste, Franc, Alain, Plancade, Sandra, Sabbadin, Régis   +5 more
openaire   +2 more sources