'dplyr' Verbs for Lists and Other Verbs for Data Frames
Provides 'dplyr' verbs for lists and other useful
verbs for manipulation of data frames. In particular, it includes a
mutate_which() function that mutates columns for a specific subset of
rows defined by a condition, and fuse() which is a more flexible version
of 'tidyr' unite() function.

Local Polynomial Estimator in Measurement Error Models
Haiming Zhou <zhouh@email.sc.edu> and Xianzheng Huang <huang@stat.sc.edu>
Two local polynomial estimators for solving the errors-in-variables problem: one is in Delaigle, Fan, and Carroll (2009), and one is in Huang and Zhou (2014+). The SIMEX bandwidth selection method is also provided for both estimators.

Local Polynomial Estimators in Measurement Error Models
Haiming Zhou <zhouh@niu.edu> and Xianzheng Huang <huang@stat.sc.edu>
Provide local polynomial estimators for nonparametric mean regression and nonparametric modal regression in the presence/absence of measurement error. Bandwidth selection is also provided for each estimator.

Nonparametric Estimation of Measurement Error Models
Provide nonparametric methods for mean regression model, modal regression and conditional density estimation in the presence/absence of measurement error. Bandwidth selection is also provided for each method.
Rcpp (>= 0.11.1), decon, flexmix, splines, locpol

Provide nonparametric methods for mean regression model, modal regression and conditional density estimation in the presence/absence of measurement error. Bandwidth selection is also provided for each method. See Huang and Zhou (2017) <doi:10.1080/10485252.2017.1303060>, Zhou and Huang (2016) <doi:10.1214/16-EJS1210>, Huang and Zhou (2020) <doi:10.1214/20-EJS1688>, and Zhou and Huang (2019) <doi:10.1080/03610918.2017.1402044>.

Modeler for linear programs (LP) and mixed integer linear
programs (MILP)
lpmodeler is a set of user-friendly functions to simplify the modelling of linear programs (LP) and mixed integer programs (MIP). It provides a unified interface compatible with optimization packages: Rsymphony.