The Annals of Applied Statistics, Vol. 15, No. 1 (March 2021), pp. 391-411 (21 pages) Gene expression deconvolution is a powerful tool for exploring the microenvironment of complex tissues comprised ...
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 ...
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 ...
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 ...
Flood damage processes are complex and vary between events and regions. State‐of‐the‐art flood loss models are often developed on the basis of empirical damage data from specific case studies and do ...
RIT computing students and Professor Rui Li are working on a National Institutes of Health-funded project to use AI in ...
Random Coefficient Modelling of the Global Effect of Exchange and Monetary Policy Rates on Inflation
This research evaluates the effect of monetary policy rate and exchange rate on inflation across continents using both Frequentist and Bayesian Generalized Additive Mixed Models (GAMMs). Extending an ...
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 ...
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