Longitudinal data analysis is an essential statistical approach for studying phenomena observed repeatedly over time, allowing researchers to explore both within-subject and between-subject variations ...

A new study introduces a global probabilistic forecasting model that predicts when and where ionospheric disturbances—measured by the Rate of total electron content (TEC) Index (ROTI)—are likely to ...

Empirical Bayes is a versatile approach to “learn from a lot” in two ways: first, from a large number of variables and, second, from a potentially large amount of prior information, for example, ...

This is a preview. Log in through your library . Abstract Since longitudinal and survival data are often obtained together in applications, studies on joint modelling that reveal the relationship ...

In this video from PyCon Australia, Rhydwyn McGuire from the The New South Wales Department of Health presents: Video: Fast, Beautiful and Easy Bayesian Modeling – Can You have it all? Bayesian models ...

A novel Bayesian Hierarchical Network Model (BHNM) is designed for ensemble predictions of daily river stage, leveraging the spatial interdependence of river networks and hydrometeorological variables ...

Dr. James McCaffrey of Microsoft Research says the main advantage of using Gaussian naive Bayes classification compared to other techniques like decision trees or neural networks is that you don't ...

Dilaton (EMD) holographic QCD model combined with Bayesian analysis to conduct a detailed investigation into the thermodynamic properties and dissociation processes of heavy quarkonium as it traverses ...

Dr. James McCaffrey of Microsoft Research shows how to predict a person's sex based on their job type, eye color and country of residence. Naive Bayes classification is a classical machine learning ...

Incrementality testing in Google Ads is suddenly within reach for far more advertisers than before. Google has lowered the barriers to running these tests, making lift measurement possible even ...