Title: Regression Analysis of Sparse Asynchronous Longitudinal Data
Author: Hongyuan Cao, Donglin Zeng, Jason P. Fine, and Shannon T. Holloway
Maintainer: Shannon T. Holloway <sthollow@ncsu.edu>
Description: Estimation of regression models for sparse asynchronous longitudinal observations, where time-dependent response and covariates are mismatched and observed intermittently within subjects. Kernel weighted estimating equations are used for generalized linear models with either time-invariant or time-dependent coefficients.

Author: Hongyuan Cao, Donglin Zeng, Jialiang Li, Jason P. Fine, and Shannon T. Holloway
Depends: compiler, parallel, stats, graphics, methods

Description: Estimation of regression models for sparse asynchronous longitudinal observations, where time-dependent response and covariates are mismatched and observed intermittently within subjects. Kernel weighted estimating equations are used for generalized linear models with either time-invariant or time-dependent coefficients. Cao, H., Li, J., and Fine, J. P. (2016) <doi:10.1214/16-EJS1141>. Cao, H., Zeng, D., and Fine, J. P. (2015) <doi:10.1111/rssb.12086>.

Author: Hongyuan Cao, Donglin Zeng, Jialiang Li, Jason P. Fine, and
Maintainer: Shannon T. Holloway <shannon.t.holloway@gmail.com>
Description: Estimation of regression models for sparse asynchronous
longitudinal observations, where time-dependent response and covariates
are mismatched and observed intermittently within subjects. Kernel
weighted estimating equations are used for generalized linear models
with either time-invariant or time-dependent coefficients. Cao, H.,

Title: A GTK GUI for teaching basic concepts in statistical inference,
Maintainer: Yvonnick Noel, University of Brittany, France
Description: A collection of statistical simulation and computation tools with a GTK GUI, to help teach statistical concepts and compute probabilities. Two domains are covered: I. Understanding (Central-Limit Theorem and the Normal Distribution, Distribution of a sample mean, Distribution of a sample variance, Probability calculator for common distributions), and II. Elementary Bayesian Statistics (bayesian inference on proportions, contingency tables, means and variances, with informative and noninformative priors).
Depends: proto, cairoDevice, gWidgetsRGtk2, partitions