Results 11 to 20 of about 13,834 (194)

Bayesian Estimation of Conditional Independence Graphs Improves Functional Connectivity Estimates. [PDF]

open access: yesPLoS Computational Biology, 2015
Functional connectivity concerns the correlated activity between neuronal populations in spatially segregated regions of the brain, which may be studied using functional magnetic resonance imaging (fMRI).
Max Hinne   +3 more
doaj   +1 more source

Mind the Queue: A Case Study in Visualizing Heterogeneous Behavioral Patterns in Livestock Sensor Data Using Unsupervised Machine Learning Techniques

open access: yesFrontiers in Veterinary Science, 2020
Sensor technologies allow ethologists to continuously monitor the behaviors of large numbers of animals over extended periods of time. This creates new opportunities to study livestock behavior in commercial settings, but also new methodological ...
Catherine McVey   +4 more
doaj   +1 more source

Causal Factors of Anxiety and Depression in College Students: Longitudinal Ecological Momentary Assessment and Causal Analysis Using Peter and Clark Momentary Conditional Independence

open access: yesJMIR Mental Health, 2020
BackgroundAcross college campuses, the prevalence of clinically relevant depression or anxiety is affecting more than 27% of the college population at some point between entry to college and graduation.
Huckins, Jeremy F   +9 more
doaj   +1 more source

Determinants of Sustainability Reporting in the Romanian Banking Sector [PDF]

open access: yesAudit Financiar
This paper investigates the determinants of Sustainable Development Goals (SDG) reporting in the Romanian banking sector over an extended time horizon (2017-2023), employing a mixed-method approach that combines content analysis, fixed-effects regression,
Mihaela CUREA   +2 more
doaj   +1 more source

randomLCA: An R Package for Latent Class with Random Effects Analysis

open access: yesJournal of Statistical Software, 2017
Latent class is a method for classifying subjects, originally based on binary outcome data but now extended to other data types. A major difficulty with the use of latent class models is the presence of heterogeneity of the outcome probabilities within ...
Ken J. Beath
doaj   +1 more source

A max-stable process model for rainfall extremes at different accumulation durations

open access: yesWeather and Climate Extremes, 2016
A common existing approach to modeling rainfall extremes employs a spatial Bayesian hierarchical model, where latent Gaussian processes are specified on distributional parameters in order to pool spatial information.
Alec G. Stephenson   +2 more
doaj   +1 more source

A Directional-Linear Bayesian Network and Its Application for Clustering and Simulation of Neural Somas

open access: yesIEEE Access, 2019
Neural somas perform most of the metabolic activities in the neuron and support the chemical process that generates the basic elements of the synapses, and consequently the brain activity.
Sergio Luengo-Sanchez   +2 more
doaj   +1 more source

Bayesian Covariance Structure Modeling of Responses and Process Data

open access: yesFrontiers in Psychology, 2019
A novel Bayesian modeling framework for response accuracy (RA), response times (RTs) and other process data is proposed. In a Bayesian covariance structure modeling approach, nested and crossed dependences within test-taker data (e.g., within a testlet ...
Konrad Klotzke, Jean-Paul Fox
doaj   +1 more source

What Is a Causal Graph?

open access: yesAlgorithms
This article surveys the variety of ways in which a directed acyclic graph (DAG) can be used to represent a problem of probabilistic causality. For each of these ways, we describe the relevant formal or informal semantics governing that representation ...
Philip Dawid
doaj   +1 more source

A local independence number condition for n-extendable graphs

open access: yesDiscrete Mathematics, 1999
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +1 more source

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