Title: Moisture Sorption Isotherm Modeling Program
Authors@R: c(person("John Carlo", "Panganiban", email = "jcfpanganiban@iskolarngbayan.pup.edu.ph", role = "aut", comment = c(ORCID = "0000-0002-0767-0598")), person("Ronald Benz", "Rivera", email = "rblrivera@iskolarngbayan.pup.edu.ph", role = "aut", comment = c(ORCID = "0000-0003-1122-2314")), person("Kim", "Villacorte", email = "kmvillacorte@iskolarngbyan.pup.edu.ph", role = "aut", comment = c(ORCID = "0000-0002-4412-7439")), person("Chester", "Deocaris", email = "ccdeocaris@pup.edu.ph", role = c("aut", "ths", "cre"), comment = c(ORCID = "0000-0003-4504-160X")))
Description: Contains sixteen moisture sorption isotherm models, which evaluate the fitness of adsorption and desorption curves for further understanding of the relationship between moisture content and water activity. Fitness evaluation is conducted through parameter estimation and error analysis. Moreover, graphical representation, hysteresis area estimation, and isotherm classification through the equation of Blahovec & Yanniotis (2009) <doi:10.1016/j.jfoodeng.2008.08.007> which is based on the classification system introduced by Brunauer et. al. (1940) <doi:10.1021/ja01864a025> are also included for the visualization of models and hysteresis.
Imports: ggplot2, Metrics, minpack.lm, nls2, stats
Author: John Carlo Panganiban [aut] (<https://orcid.org/0000-0002-0767-0598>),
Ronald Benz Rivera [aut] (<https://orcid.org/0000-0003-1122-2314>),

Title: High-Dimensional Variable Selection with Presence-Only Data
Authors@R: c(person("Hyebin", "Song", role = c("aut", "cre"),
Description: Efficient algorithm for solving PU (Positive and Unlabelled) problem in low or high dimensional setting with lasso or group lasso penalty. The algorithm uses Maximization-Minorization and (block) coordinate descent. Sparse calculation and parallel computing via 'OpenMP' are supported for the computational speed-up. See Hyebin Song, Garvesh Raskutti (2017) <arXiv:1711.08129>.
LinkingTo: Rcpp, BH, bigmemory, RcppEigen