Alkes Price, Po-Ru Loh and colleagues report the BOLT-LMM method for mixed-model association. They apply their method to 9 quantitative traits in 23,294 samples and demonstrate that it provides ...

In objective Bayesian model selection, no single criterion has emerged as dominant in defining objective prior distributions. Indeed, many criteria have been separately proposed and utilized to ...

This paper extends the Bayesian Model Averaging framework to panel data models where the lagged dependent variable as well as endogenous variables appear as regressors. We propose a Limited ...

We apply a linear Bayesian model to seismic tomography, a high-dimensional inverse problem in geophysics. The objective is to estimate the three-dimensional structure of the earth's interior from data ...

Inequality of opportunity has great normative importance. This has led to a literature on measuring the part of overall inequality that is due to circumstances outside of a person’s control. We ...

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 ...

When estimating DSGE models, the number of observable economic variables is usually kept small, and it is conveniently assumed that DSGE model variables are perfectly measured by a single data series.

A study of over 6,800 patients identifies key pathways driving severe asthma exacerbation risk, highlighting roles for eosinophils, FeNO, and FEV₁.

Using Bayesian models, you can add your past knowledge about how your media performs into Meridian. This includes insights from previous experiments, other marketing mix models, industry know-how ...