Title: Asymptotically Bias-Corrected Regularized Linear Discriminant
person("Dmitriy", "Fedorov", email = "dmitriy.fedorov@nu.edu.kz", role = c("aut", "cre")),
person("Amin", "Zollanvari", email = "amin.zollanvari@nu.edu.kz", role = "aut"),
person("Aresh", "Dadlani", email = "aresh.dadlani@nu.edu.kz ", role = "aut"),
person("Berdakh", "Abibullaev", email = "berdakh.abibullaev@nu.edu.kz", role = "aut"))
Description: Offers methods to perform asymptotically bias-corrected regularized linear discriminant analysis (ABC_RLDA) for cost-sensitive binary classification. The bias-correction is an estimate of the bias term added to regularized discriminant analysis (RLDA) that minimizes the overall risk. The default magnitude of misclassification costs are equal and set to 0.5; however, the package also offers the options to set them to some predetermined values or, alternatively, take them as hyperparameters to tune.
A. Zollanvari, M. Abdirash, A. Dadlani and B. Abibullaev (2019) <doi:10.1109/LSP.2019.2918485>.

Title: Algorithms for ABC summary statistics selection
Description: Methods for choosing summary statistics in approximate

Description: Tools for approximate Bayesian computation including summary statistic selection and assessing coverage
Depends: R (>= 2.10), abc, abind, parallel, pls, plyr

Description: Tools for approximate Bayesian computation including
summary statistic selection and assessing coverage

Description: Tools for approximate Bayesian computation including summary statistic selection and assessing coverage.
Depends: R (>= 2.10), abc, abind, parallel, plyr

Depends: R (>= 2.10), abc, abind, parallel, plyr, Hmisc

Author: Kevin M. Middleton <kmm@csusb.edu>, Randall Pruim
Maintainer: Kevin M. Middleton <kmm@csusb.edu>, Randall Pruim
Depends: R (>= 2.10), nlme, lattice, grid
Suggests: boot, car, ggplot2, HH, plyr, vcd, Hmisc
Description: The abd package contains data sets and sample code for the
book, The Analysis of Biological Data by Michael Whitlock and
Dolph Schluter (2009; Roberts & Company Publishers).