Regression Analysis of Sparse Asynchronous Longitudinal Data
Hongyuan Cao, Donglin Zeng, Jason P. Fine, and Shannon T. Holloway
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.

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

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>.

Hongyuan Cao, Donglin Zeng, Jialiang Li, Jason P. Fine, and
Shannon T. Holloway
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>.

A GTK GUI for teaching basic concepts in statistical inference,
and doing elementary bayesian tests.
Yvonnick Noel, University of Brittany, France
<yvonnick.noel@univ-rennes2.fr>
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).