Commercial motor vehicle driver fatigue, long-term health, and highway safety: research needs
National Academies of Sciences… - 2016 - books.google.com
There are approximately 4,000 fatalities in crashes involving trucks and buses in the United
States each year. Though estimates are wide-ranging, possibly 10 to 20 percent of these …
States each year. Though estimates are wide-ranging, possibly 10 to 20 percent of these …
Joint estimation of behind-the-meter solar generation in a community
Distribution grid planning, control, and optimization require accurate estimation of solar
photovoltaic (PV) generation and electric load in the system. Most of the small residential …
photovoltaic (PV) generation and electric load in the system. Most of the small residential …
Go multivariate: recommendations on Bayesian multilevel hidden Markov models with categorical data
S Mildiner Moraga, E Aarts - Multivariate Behavioral Research, 2024 - Taylor & Francis
The multilevel hidden Markov model (MHMM) is a promising method to investigate intense
longitudinal data obtained within the social and behavioral sciences. The MHMM quantifies …
longitudinal data obtained within the social and behavioral sciences. The MHMM quantifies …
On the use of mixed Markov models for intensive longitudinal data
S de Haan-Rietdijk, P Kuppens… - Multivariate …, 2017 - Taylor & Francis
Markov modeling presents an attractive analytical framework for researchers who are
interested in state-switching processes occurring within a person, dyad, family, group, or …
interested in state-switching processes occurring within a person, dyad, family, group, or …
Bayesian hidden Markov modelling using circular‐linear general projected normal distribution
We introduce a multivariate hidden Markov model to jointly cluster time‐series observations
with different support, that is, circular and linear. Relying on the general projected normal …
with different support, that is, circular and linear. Relying on the general projected normal …
Bayesian mixed-effect higher-order hidden Markov models with applications to predictive healthcare using electronic health records
The disease progression dynamics observed in electronic health records often reflect
patients' health condition evolution, holding the promise of enabling the development of …
patients' health condition evolution, holding the promise of enabling the development of …
Multivariate generalized hidden Markov regression models with random covariates: physical exercise in an elderly population
A time‐varying latent variable model is proposed to jointly analyze multivariate mixed‐
support longitudinal data. The proposal can be viewed as an extension of hidden Markov …
support longitudinal data. The proposal can be viewed as an extension of hidden Markov …
Sample size considerations for bayesian multilevel hidden markov models: A simulation study on multivariate continuous data with highly overlapping component …
Spurred in part by the ever-growing number of sensors and web-based methods of
collecting data, the use of Intensive Longitudinal Data (ILD) is becoming more common in …
collecting data, the use of Intensive Longitudinal Data (ILD) is becoming more common in …
Novel driver behavior model analysis using hidden Markov model to increase road safety in smart cities
The ability to categorize the driver behavior is very essential for advance driver assistance
system (ADAS). A method for identifying driver's behavior is important to assist operative …
system (ADAS). A method for identifying driver's behavior is important to assist operative …
A Bayesian multilevel hidden Markov model with Poisson-lognormal emissions for intense longitudinal count data
Hidden Markov models (HMMs) are probabilistic methods in which observations are seen as
realizations of a latent Markov process with discrete states that switch over time. Moving …
realizations of a latent Markov process with discrete states that switch over time. Moving …