Title: Goodness-of-Fit Tests using Kernelized Stein Discrepancy
Authors@R: c(person("Min Hyung", "Kang", role = c("aut","cre"), email = "Minhyung.Daniel.Kang@gmail.com"),person("Qiang", "Liu",role="aut",email="qliu@cs.dartmouth.edu"))
Description: An adaptation of Kernelized Stein Discrepancy, this package provides a goodness-of-fit test of whether a given i.i.d. sample is drawn from a given distribution. It works for any distribution once its score function (the derivative of log-density) can be provided. This method is based on "A Kernelized Stein Discrepancy for Goodness-of-fit Tests and Model Evaluation" by Liu, Lee, and Jordan, available at <http://arxiv.org/abs/1602.03253>.

Description: An adaptation of Kernelized Stein Discrepancy, this package provides a goodness-of-fit test of whether a given i.i.d. sample is drawn from a given distribution. It works for any distribution once its score function (the derivative of log-density) can be provided. This method is based on "A Kernelized Stein Discrepancy for Goodness-of-fit Tests and Model Evaluation" by Liu, Lee, and Jordan, available at <arXiv:1602.03253>.
Packaged: 2021-01-11 07:33:36 UTC; danielkang

Description: Infers relative kinase activity from phosphoproteomics data
using the method described by Casado et al. (2013) <doi:10.1126/scisignal.2003573>.
Maintainer: Danica D. Wiredja <dwiredja@gmail.com>
Imports: gplots, graphics, stats, grDevices, utils

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.
Imports: usethis, expm, CompQuadForm, DEoptim
Packaged: 2019-01-04 19:33:01 UTC; Catherine