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 ...

Scandinavian Journal of Statistics, Vol. 34, No. 4 (December 2007), pp. 816-828 (13 pages) O'Hagan (Highly Structured Stochastic Systems, Oxford University Press, Oxford, 2003) introduces some tools ...

针对生物制药尤其是多价疫苗稳定性评估耗时长、资源密集的问题，研究人员开发贝叶斯分层模型（Bayesian hierarchical model），以九价人乳头瘤病毒疫苗（GARDASIL?9）为对象，整合多批次多温度稳定性数据，精准预测效力等关键指标，为加速疫苗上市及全球可及性 ...

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 ...

BhGLM is a freely available R package that implements Bayesian hierarchical modeling for high-dimensional clinical and genomic data. It consists of functions for setting up various Bayesian ...

Here’s our estimate of public support for vouchers, broken down by religion/ethnicity, income, and state: (Click on image to see larger version.) We’re mapping estimates from a hierarchical Bayes ...

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 ...

What Is A Hierarchical Models? Hierarchical models, also known as hierarchical statistical models, multilevel models or random-effects models, are tools for analysing data with a nested or grouped ...

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 ...