Results 21 to 30 of about 255,218 (244)

Model-Based Causal Feature Selection for General Response Types [PDF]

Journal of the American Statistical Association, 2023
Discovering causal relationships from observational data is a fundamental yet challenging task. Invariant causal prediction (ICP, Peters, Bühlmann, and Meinshausen) is a method for causal feature selection which requires data from heterogeneous settings ...
Lucas Kook, Sorawit Saengkyongam, A. Lundborg, Torsten Hothorn, Jonas Peters   +4 more
semanticscholar   +1 more source

Chaoticity for multi-class systems and exchangeability within classes [PDF]

, 2008
Classical results for exchangeable systems of random variables are extended to multi-class systems satisfying a natural partial exchangeability assumption.
Graham, Carl
core   +5 more sources

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

Frontiers 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, Fushing Hsieh, Diego Manriquez, Pablo Pinedo, Kristina Horback   +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

JMIR 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, DaSilva, Alex W, Hedlund, Elin L, Murphy, Eilis I, Rogers, Courtney, Wang, Weichen, Obuchi, Mikio, Holtzheimer, Paul E, Wagner, Dylan D, Campbell, Andrew T   +9 more
doaj   +1 more source

Exploiting Causal Independence in Bayesian Network Inference [PDF]

Journal of Artificial Intelligence Research, 1996
A new method is proposed for exploiting causal independencies in exact Bayesian network inference. A Bayesian network can be viewed as representing a factorization of a joint probability into the multiplication of a set of conditional probabilities.
N. Zhang, D. Poole
semanticscholar   +1 more source

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

Audit 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, Maria Carmen HUIAN, Marilena MIRONIUC   +2 more
doaj   +1 more source

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

Journal 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

Weather 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, Eric A. Lehmann, Aloke Phatak   +2 more
doaj   +1 more source

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

IEEE 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, Pedro Larranaga, Concha Bielza   +2 more
doaj   +1 more source

Credal Networks under Epistemic Irrelevance [PDF]

, 2017
A credal network under epistemic irrelevance is a generalised type of Bayesian network that relaxes its two main building blocks. On the one hand, the local probabilities are allowed to be partially specified.
De Bock, Jasper
core   +2 more sources