Description: Implements modeling and computational tools for conditional
random fields (CRF) model as well as other probabilistic undirected
graphical models of discrete data with pairwise and unary potentials.
Authors@R: c(person("Ling-Yun", "Wu", role = c("aut", "cre"), email =

Description: This package implements modeling and computational tools for
conditional random fields model (CRF) as well as other probabilistic
undirected graphical models (UGM) of discrete data with pairwise and

undirected graphical models of discrete data with pairwise and unary

Title: Mixture Cure Generalized Odds Ratio Frailty Models for Clustered
Author: Tong Wang, Kejun He, Wei Ma, Dipankar Bandyopadhyay, Samiran Sinha
Description: A methodology to estimate the parameters for the cure rate frailty models with clustered current status data.
Imports: Rcpp (>= 0.12.18), numDeriv, splines2, orthopolynom

Title: Continual Reassessment Method (CRM) for Phase I Clinical Trials
Description: CRM simulator for Phase I Clinical Trials

Description: Functions for phase I clinical trials using the continual reassessment method.

Title: Bayesian Nonparametric Chinese Restaurant Process Clustering
person("Masashi", "Okada", role = c("aut", "cre"), email="okadaalgorithm@gmail.com")
Description: Chinese restaurant process [Pitman (1995) <doi:10.1007/BF01213386>] is used in order to compose Dirichlet process [Ferguson (1973) <doi:10.1214/aos/1176342360>]. The clustering which uses Chinese restaurant process does not need to decide the number of clusters in advance. This algorithm automatically adjusts it. And this package calculates the ambiguity of clusters as entropy [Yngvason (1999) <doi:10.1016/S0370-1573(98)00082-9>].
Imports: MASS, mvtnorm, randomcoloR, graphics, stats, utils, png

Imports: MASS, mvtnorm, randomcoloR, lucid, dplyr, graphics, stats,

Title: Conditional Randomization Testing (CRT) Approach for Conjoint
person("Dae Woong", "Ham", email = "daewoongham@g.harvard.edu", role = c("aut", "cre")),
person("Kosuke", "Imai", email = "imai@harvard.edu", role = "aut"),
person("Lucas", "Janson", email = "ljanson@fas.harvard.edu",role = "aut"),
person("Jacob", "Bien", email = "jbien@usc.edu",role = c("ctb", "cph")))
Maintainer: Dae Woong Ham <daewoongham@g.harvard.edu>
Description: Computes p-value according to the CRT using the HierNet test statistic. For more details, see Ham, Imai, Janson (2022) "Using Machine Learning to Test Causal Hypotheses in Conjoint Analysis" <arXiv:2201.08343>.
Imports: utils, methods, doSNOW, foreach, Rcpp, snow
Copyright: (c) 2022 Dae Woong Ham. Code in helper_hierNet.R, hierNet.c,
and hierNet_init.c are taken (with explicit permission) from