Package: KSPM
Title: Kernel Semi-Parametric Models
Version: 0.1.1
Authors@R: c(person("Catherine", "Schramm", email = "cath.schramm@gmail.com", role = c("aut", "cre")), person("Aurelie", "Labbe", role = "ctb"), person("Celia M. T.", "Greenwood", role = "ctb"))
Description: To fit the kernel semi-parametric model and its extensions. It allows multiple kernels and unlimited interactions in the same model. Coefficients are estimated by maximizing a penalized log-likelihood; penalization terms and hyperparameters are estimated by minimizing leave-one-out error. It includes predictions with confidence/prediction intervals, statistical tests for the significance of each kernel, a procedure for variable selection and graphical tools for diagnostics and interpretation of covariate effects. Currently it is implemented for continuous dependent variables.
Depends: R (>= 3.5.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: usethis, expm, CompQuadForm, DEoptim
Suggests: testthat
NeedsCompilation: no
Packaged: 2019-02-01 16:05:58 UTC; Catherine
Author: Catherine Schramm [aut, cre],
  Aurelie Labbe [ctb],
  Celia M. T. Greenwood [ctb]
Maintainer: Catherine Schramm <cath.schramm@gmail.com>
Repository: CRAN
Date/Publication: 2019-02-01 17:33:30 UTC
