Packaged: 2019-05-30 21:08:43 UTC; julienvollering

Packaged: 2020-04-14 21:24:51 UTC; julienvollering

person("Julien", "Vollering", email = "julienvollering@gmail.com", role = c("aut", "cre")),
person("Sabrina", "Mazzoni", role = "aut"),
person("Rune", "Halvorsen", role = "aut"),

Title: The Computing of Monotonic Spline Bases and Constrained
Authors@R: c(person("Yili", "Hong", role = c("aut", "cre"),email = "yilihong@vt.edu"),person("Jie", "Min", role = c("aut", "ctb")))
Description: Providing C implementation for the computing of monotonic spline bases, including M-splines, I-splines, and C-splines, denoted by MIC splines. The definitions of the spline bases are described in Meyer (2008) <doi: 10.1214/08-AOAS167>. The package also provides the computing of constrained least-squares estimates when a subset of or all of the regression coefficients are constrained to be non-negative.

Title: Microcluster-Based Detector of Anomalies in Edge Streams
Description: This is a wrapper around the C++ implementation of 'MIDAS' (Bhatia et al., 2020) <https://www.comp.nus.edu.sg/~sbhatia/assets/pdf/midas.pdf> by Siddharth Bhatia for graph like data.

Title: Nearly Exact Sample Size Calculation for Exact Powerful
Nonrandomized Tests for Differences Between Binomial
Description: Implementation of the mid-n algorithms presented in
Wellek S (2015) <DOI:10.1111/stan.12063> Statistica Neerlandica 69, 358-373 for exact
sample size calculation for superiority trials with binary outcome.

Title: Multiple Imputation for interval censored data regression
Description: Applies the Pan's (2000) multiple imputation approach to Cox or Fine and Gray regression for interval censored data.
Depends: mstate , prodlim, cmprsk, riskRegression

Title: Data Augmentation and Multiple Imputation for Interval Censored
Authors@R: person("Marc", "Delord", , "mdelord@gmail.com", role = c("aut", "cre"))
Description: Implements data augmentation schemes with multiple imputation steps for proportional hazards regression with interval censored data or proportional subdistribution hazards regression for interval censored competing risks data. The main functions allow to estimate survival function, cumulative incidence function, Cox and Fine & Gray regression coefficients and associated variance-covariance matrix. MIICD functions call Surv, survfit and coxph from survival package, FGR from riskRegression package, and mvrnorm from the MASS package.