Title: Optimal Designs for Nonlinear Models
Description: Finds optimal designs for nonlinear models using a metaheuristic algorithm called imperialist competitive algorithm ICA. See, for details, Masoudi et al. (2017) <doi:10.1016/j.csda.2016.06.014>.
Imports: Rcpp, nloptr, stats, graphics, grDevices, cubature, sn,
Suggests: rgl, lattice, knitr, rmarkdown

Description: Finds optimal designs for nonlinear models using a metaheuristic algorithm called imperialist competitive algorithm ICA. See, for details, Masoudi et al. (2017) <doi:10.1016/j.csda.2016.06.014> and Masoudi et al. (2019) <doi:10.1080/10618600.2019.1601097>.

Title: Optimal Designs for Linear and Nonlinear Models
Authors@R: c(person("Ehsan", "Masoudi", role = c("aut", "cre"),  email = "esn_mud@yahoo.com"),  person("Heinz", "Holling", role = "aut"),  person("Weng Kee", "Wong", role = "aut"), person("Seongho", "Kim", role = c("ctb")))
Imports: Rcpp, nloptr, stats, utils, graphics, grDevices, cubature, sn,

Title: Optimal Designs for Nonlinear Statistical Models by Imperialist
Description: Finds optimal designs for nonlinear models using a metaheuristic algorithm called Imperialist Competitive Algorithm (ICA). See, for details, Masoudi et al. (2017) <doi:10.1016/j.csda.2016.06.014> and Masoudi et al. (2019) <doi:10.1080/10618600.2019.1601097>.

Title: Bayesian Semiparametric Models for Interval-Censored Data
Author: Chun Pan, Bo Cai, Lianming Wang, and Xiaoyan Lin
Description: Contains functions to fit Bayesian semiparametric regression survival models (proportional hazards model, proportional odds model, and probit model) to interval-censored time-to-event data.
Packaged: 2015-11-27 21:36:46 UTC; xiaoluobo

Title: Data-Driven Design of Targeted Gene Panels for Estimating
Description: Implementation of the methodology proposed in 'Data-driven design of targeted gene panels for estimating immunotherapy biomarkers', Bradley and Cannings (2021) <arXiv:2102.04296>. This package allows the user to fit generative models of mutation from an annotated mutation dataset, and then further to produce tunable linear estimators of exome-wide biomarkers. It also contains functions to simulate mutation annotated format (MAF) data, as well as to analyse the output and performance of models.
Imports: stats, utils, glmnet, Matrix, dplyr, purrr, latex2exp,
Author: Jacob R. Bradley [aut, cre] (<https://orcid.org/0000-0003-1616-4969>),
Timothy I. Cannings [aut] (<https://orcid.org/0000-0002-2111-4168>)
Maintainer: Jacob R. Bradley <cobrbradley@gmail.com>