Title: Bayesian Modeling via Goodness of Fit
Author: Subhadeep Mukhopadhyay, Douglas Fletcher
Description: Non-parametric method for learning prior distribution starting with parametric (subjective) prior.  It performs four interconnected tasks: (i) characterizes the uncertainty of the elicited prior; (ii) exploratory diagnostic for checking prior-data conflict; (iii) computes the final statistical prior density estimate; and (iv) performs macro- and micro-inference. Primary reference is Mukhopadhyay, S. and Fletcher, D. (2017, Technical Report).

Description: A Bayesian data modeling scheme that performs four interconnected tasks: (i) characterizes the uncertainty of the elicited parametric prior; (ii) provides exploratory diagnostic for checking prior-data conflict; (iii) computes the final statistical prior density estimate; and (iv) executes macro- and micro-inference. Primary reference is Mukhopadhyay, S. and Fletcher, D. (2018, Technical Report, <arXiv:1802.00474>).

Title: Bayesian Modeling via Goodness-of-Fit
Depends: orthopolynom, VGAM, Bolstad2, nleqslv

Description: A Bayesian data modeling scheme that performs four interconnected tasks: (i) characterizes the uncertainty of the elicited parametric prior; (ii) provides exploratory diagnostic for checking prior-data conflict; (iii) computes the final statistical prior density estimate; and (iv) executes macro- and micro-inference. Primary reference is Mukhopadhyay, S. and Fletcher, D. 2018 paper "Generalized Empirical Bayes via Frequentist Goodness of Fit" (<https://www.nature.com/articles/s41598-018-28130-5 >).

Title: Bayesian Modeling via Frequentist Goodness-of-Fit

Title: Fast Bayesian Gaussian Process Regression Fitting
Description: Bayesian inferences on nonparametric regression via Gaussian Processes with a modified exponential square kernel using a basis expansion approach.

Title: Bayesian Grouped Weighted Quantile Sum Regression
Description: Fits Bayesian grouped weighted quantile sum (BGWQS) regressions for one or more chemical groups with binary outcomes. Wheeler DC et al. (2019) <doi:10.1016/j.sste.2019.100286>. Wheeler DC et al. (2020) <doi:10.3390/ijerph17082864>.
Packaged: 2020-06-07 19:39:21 UTC; Matt Carli