Description: JOP is a tool for simultanous optimization of multiple
responses and visualization of the results. The visualization
is done by the joint optimization plot introduced by Kuhnt and

Depends: Rsolnp, rgenoud, stats, JointModeling

Description: JOP is a tool for simultaneous optimization of multiple

Title: Practical Smoothing with P-Splines
Authors@R: c(person(given = "Paul", family = "Eilers", role = c("aut", "cre"), email = "p.eilers@erasmusmc.nl"),
person(given = "Brian", family = "Marx", role = "aut", email = "p.eilers@erasmusmc.nl"),
person(given = "Bin", family = "Li", email = "bli@lsu.edu",  role = "aut"),
person(given = "Jutta", family = "Gampe", email = "gampe@demogr.mpg.de",  role = "aut"),
person(given = "Maria Xose", family = "Rodriguez-Alvarez", email = "mrodriguez@BCAMATH.ORG",  role = "aut"))
Description: Functions and data to reproduce all plots in the book "Practical Smoothing.
The Joys of P-splines" by Paul H.C. Eilers and Brian D. Marx (2021, ISBN:978-1108482950).
Imports: colorspace, MASS, boot, fds, rpart, ggplot2, fields, spam,

person(given = "Brian", family = "Marx", role = "aut", email = "bmarx@lsu.edu"),

Title: Implements Under/Oversampling for Probability Estimation
Authors@R: person("Matthew", "Olson", , "maolson@wharton.upenn.edu", c("aut", "cre"))
Description: Implements under/oversampling for probability estimation.  To be
used with machine learning methods such as adaBoost, random forests, etc.
Packaged: 2016-09-12 14:15:05 UTC; matthewolson

Imports: Rcpp, rpart, stats, doParallel, foreach
Packaged: 2017-05-23 16:37:22 UTC; matthewolson

used with machine learning methods such as AdaBoost, random forests, etc.
Packaged: 2017-07-12 18:16:22 UTC; matthewolson

Title: Covariance and Inverse Covariance Matrix Estimation Using Joint
Description: A Joint PENalty Estimation of Covariance and Inverse Covariance Matrices.

Title: Methods for population-based cancer survival analysis
Description: Functions, methods, and datasets for cancer survival
analysis, including the proportional hazard relative survival
model, the join point relative survival model.