Bin Dai

Bin Dai

3 packages on CRAN

MVB

cran
99.99th

Percentile

Fit log-linear model for multivariate Bernoulli distribution with mixed effect models and LASSO

lme4

cran
99.99th

Percentile

Fit linear and generalized linear mixed-effects models. The models and their components are represented using S4 classes and methods. The core computational algorithms are implemented using the 'Eigen' C++ library for numerical linear algebra and 'RcppEigen' "glue".

oem

cran
99.99th

Percentile

Solves penalized least squares problems for big tall data using the orthogonalizing EM algorithm of Xiong et al. (2016) <doi:10.1080/00401706.2015.1054436>. The main fitting function is oem() and the functions cv.oem() and xval.oem() are for cross validation, the latter being an accelerated cross validation function for linear models. The big.oem() function allows for out of memory fitting.