https://doi.org/10.1525/auk.2009.09015 • https://www.jstor.org/stable/10.1525/auk.2009.09015 Copy URL Abstract Models for estimating survival probability of nests ...

We adapt a semi-Bayesian hierarchical modeling framework to jointly characterize the space–time variability of seasonal precipitation totals and precipitation extremes across the Northern Great Plains ...

The factor model is an important construct for both portfolio managers and researchers in modern finance. For practitioners, factor model coefficients are used to guide the construction of optimal ...

A Bayesian hierarchical model was developed to estimate the parameters in a physiologically based pharmacokinetic (PBPK) model for chloroform using prior information and biomarker data from different ...

Machine Learning gets all the marketing hype, but are we overlooking Bayesian Networks? Here's a deeper look at why "Bayes Nets" are underrated - especially when it comes to addressing probability and ...

Osaka, Japan - Scientists from the Institute of Scientific and Industrial Research, and NTN Next Generation Research Alliance Laboratories at Osaka University developed a machine learning method that ...

We present a spatial Bayesian hierarchical model for seasonal extreme precipitation. At the first level of hierarchy, the seasonal maximum precipitation (i.e. block maxima) at any location is assumed ...

Eligible patients were treated daily with imatinib dosed at 300 mg twice a day (for body-surface area ≥ 1.5 m 2). The primary end point was response (clinical benefit response [CBR]), defined as ...