Title: Relative Risk Regression Using the Log-Binomial Model
Description: Methods for fitting log-link GLMs and GAMs to binomial data,

including EM-type algorithms with more stable convergence properties than standard methods.
person("Ian C.", "Marschner", rol = "ths"),
person("Alexandra C.", "Gillett", rol = "ctb", comment = "wrote an initial version of the nplbin function"))
Alexandra C. Gillett [ctb] (wrote an initial version of the nplbin

Authors@R: c(person("Mark W.", "Donoghoe", email = "markdonoghoe@gmail.com", role = c("aut","cre"),
person("Ian C.", "Marschner", role = "ths",
person("Alexandra C.", "Gillett", role = "ctb",
comment = c("wrote an initial version of the nplbin function",
Imports: splines, glm2, turboEM (>= 2021.1), Matrix, itertools2,
Author: Mark W. Donoghoe [aut, cre] (<https://orcid.org/0000-0003-0212-6443>),

person("Alexandra C.", "Gillett", rol = "ctb", comment = "Wrote an initial version of the nplbin function"))
Alexandra C. Gillett [ctb] (Wrote an initial version of the nplbin

Title: CoxPH Model with Log Concave Baseline Distribution
Description: Computes a cox PH model with a log concave baseline distribution. If no covariates are provided, estimates the log concave NPMLE. Built specifically for interval censored data, where data is a n by 2 matrix with [i, 1] as the left side of the interval for subject i and [i,2] as right side. Uncensored data can be entered by setting [i,1] = [i,2]. Alternatively, this can also handle uncensored data. If all the data is uncensored, you may enter data as a length(n) vector.

Title: Maximum likelihood estimation of a log-concave density based on
Author: Dominic Schuhmacher <schuhmacher@stat.unibe.ch>, Kaspar
Depends: R (>= 2.10.0), base, methods, utils, grDevices, graphics,
Description: Based on right or interval censored data, compute the
maximum likelihood estimator of a density under the assumption
that it is log-concave. For further information see Duembgen,
Schuhmacher, and Rufibach (2011, preprint).

Author: Dominic Schuhmacher <dominic.schuhmacher@mathematik.uni-goettingen.de>, Kaspar Rufibach <kaspar.rufibach@gmail.com>, Lutz Duembgen <duembgen@stat.unibe.ch>
Depends: R (>= 2.15.0), base, methods, utils, grDevices, graphics,
Description: Based on right or interval censored data, compute the maximum likelihood estimator of a (sub)probability density under the assumption that it is log-concave. For further information see Duembgen, Rufibach, and Schuhmacher (2011, preprint).