Title: Condition Number Regularized Covariance Estimation
Author: Sang-Yun Oh <sangoh@stanford.edu>, Bala Rajaratnam

Author: Sang-Yun Oh <syoh@lbl.gov>, Joong-Ho Won <wonj@stats.snu.ac.kr>

Title: Censored Data Imputation for Direct Modeling
person("Yizhuo", "Wang", role=c("aut", "cre"), email="ywang70@mdanderson.org", comment = c(ORCID = "0000-0002-1870-0019")),
Description: Impute the survival times for censored observations based on their conditional survival distributions derived from the Kaplan-Meier estimator. 'CondiS' can replace the censored observations with the best approximations from the statistical model, allowing for direct application of machine learning-based methods. When covariates are available, 'CondiS' is extended by incorporating the covariate information through machine learning-based regression modeling ('CondiS_X'), which can further improve the imputed survival time.
Imports: caret, survival, kernlab, purrr, tidyverse, survminer
Author: Yizhuo Wang [aut, cre] (<https://orcid.org/0000-0002-1870-0019>),

Title: Confidence Interval for the Univariate Population Variance
Description: Surrounds the usual sample variance of a univariate numeric sample with a confidence interval for the population variance. This has been done so far only under the assumption that the underlying distribution is normal. Under the hood, this package implements the unique least-variance unbiased estimator of the variance of the sample variance, in a formula that is equivalent to estimating kurtosis and square of the population variance in an unbiased way and combining them according to the classical formula into an estimator of the variance of the sample variance. Both the sample variance and the estimator of its variance are U-statistics. By the theory of U-statistic, the resulting estimator is unique. See Fuchs, Krautenbacher (2016) <doi:10.1080/15598608.2016.1158675> and the references therein for an overview of unbiased estimation of variances of U-statistics.

Title: Package to Parse an INI File, Including Variable Interpolation
Authors@R: person("Holger", "Hoefling", email = "hhoeflin@gmail.com", role = c("aut", "cre"))
Description: Enhances the 'ini' package by adding the ability to interpolate variables.
The INI configuration file is read into an R6 ConfigParser object (loosely inspired by Pythons ConfigParser module)
and the keys can be read, where '%(....)s' instances are interpolated by other included options or outside variables.