Description: Toggle R interactive mode by setting C level global

Title: Cure Rate Estimators for Interval Censored Data
Authors@R: person("Julio", "Brettas", email = "jbrettas@ime.usp.br",
Description: Implementations of semiparametric cure rate estimators for interval
censored data in R. The algorithms are based on the promotion time and
frailty models, all for interval censoring. For the frailty model,
there is also a implementation contemplating clustered data.
Imports: foreach, survival, MASS, stats4, Matrix, iterators, parallel

Title: Interaction Analysis of Repeated Measure Data
Author: Fei Zhou, Yinhao Du, Jie Ren, Xiaoxi Li, Cen Wu
Description: Extensive penalized variable selection methods have been developed in the past two decades for analyzing high dimensional omics data, such as gene expressions, single nucleotide polymorphisms (SNPs), copy number variations (CNVs) and others. However, lipidomics data have been rarely investigated by using high dimensional variable selection methods. This package incorporates our recently developed penalization procedures to conduct interaction analysis for high dimensional lipidomics data with repeated measurements. A new upgraded version will be released in the near future. The development of this software package and the associated statistical methods have been partially supported by an Innovative Research Award from Johnson Cancer Research Center, Kansas State University.

Title: Interaction Analysis of Repeatedly Measured Data
Author: Fei Zhou, Jie Ren, Xiaoxi Li, Cen Wu, Yu Jiang
Description: Extensive penalized variable selection methods have been developed in the past two decades for analyzing high dimensional omics data, such as gene expressions, single nucleotide polymorphisms (SNPs), copy number variations (CNVs) and others. However, lipidomics data have been rarely investigated by using high dimensional variable selection methods. This package incorporates our recently developed penalization procedures to conduct interaction analysis for high dimensional lipidomics data with repeated measurements. The core module of this package is developed in C++. The development of this software package and the associated statistical methods have been partially supported by an Innovative Research Award from Johnson Cancer Research Center, Kansas State University.