Bayesian Logistic Regression with Heavy-Tailed Priors
c(person(given = "Longhai", family = "Li", role = c("aut", "cre"), email = "longhai@math.usask.ca",
comment=c(ORCID="0000-0002-3074-8584")), person(given = "Steven", family = "Liu", role = c("aut"),
email = "xil865@usask.ca"))
Efficient Bayesian multinomial logistic regression based on heavy-tailed
(hyper-LASSO, non-convex) priors. The posterior of coefficients and hyper-parameters
is sampled with restricted Gibbs sampling for leveraging the high-dimensionality and
Hamiltonian Monte Carlo for handling the high-correlation among coefficients. A detailed
description of the method: Li and Yao (2018), JSCS, 88:14, 2827-2851, <arXiv:1405.3319>.
rda, ggplot2, corrplot, testthat (>= 2.0.0), bayesplot,
knitr, rmarkdown
Rcpp (>= 0.12.0), BCBCSF, glmnet, magrittr
Longhai Li [aut, cre] (<https://orcid.org/0000-0002-3074-8584>),
Steven Liu [aut]

Efficient Bayesian multinomial logistic regression based on heavy-tailed
(hyper-LASSO, non-convex) priors. The posterior of coefficients and hyper-parameters
is sampled with restricted Gibbs sampling for leveraging the high-dimensionality and
Hamiltonian Monte Carlo for handling the high-correlation among coefficients. A detailed
description of the method: Li and Yao (2018),
Journal of Statistical Computation and Simulation, 88:14, 2827-2851, <arXiv:1405.3319>.
ggplot2, corrplot, testthat (>= 2.1.0), bayesplot, knitr,
rmarkdown

Eric Lecoutre  R port by Mathieu Ros <mathieuros@bigfoot.com>
Functions for exporting R object as html tables

Facilitates automated HTML report creation
Markus Loecher, Sense Networks <markus@sensenetworks.com>
Facilitates automated HTML report creation, in particular
framed HTML pages and dynamically sortable tables.

"Markus Loecher, Berlin School of Economics and Law (BSEL)"
<markus.loecher@gmail.com>

Facilitates Automated HTML Report Creation
"Markus Loecher, Berlin School of Economics and Law (BSEL)"  <markus.loecher@gmail.com>
"Markus Loecher, Berlin School of Economics and Law (BSEL)" <markus.loecher@gmail.com>