Random forest with a variety of additional features for regression, classification and survival analysis. 
             The features include: parallel computing with OpenMP, embedded model for selecting the splitting variable,
             based on Zhu, Zeng & Kosorok (2015) <doi:10.1080/01621459.2015.1036994>, subject weight, variable weight, 
             tracking subjects used in each tree, etc.

R interface to the 'LTP'-Cloud service for Natural Language Processing
    in Chinese (http://www.ltp-cloud.com/).

A collection of functions to simulate luminescence production in 
    dosimetric materials using Monte Carlo methods. Implemented are models for 
    delocalised transitions (e.g., Chen and McKeever (1997) <doi:10.1142/2781>), 
    localised transitions (e.g., Pagonis et al. (2019) <doi:10.1016/j.jlumin.2018.11.024>) 
    and tunnelling transitions (Jain et al. (2012) <doi:10.1088/0953-8984/24/38/385402> 
    and Pagonis et al. (2019) <doi:10.1016/j.jlumin.2018.11.024>). 
    Supported stimulation methods are thermal luminescence (TL), 
    continuous-wave optically stimulated luminescence (CW-OSL), 
    linearly-modulated optically stimulated luminescence (LM-OSL), 
    linearly-modulated infrared stimulated luminescence (LM-IRSL),
    and isothermal luminescence (ITL or ISO-TL).

A collection of functions to simulate luminescence signals in quartz and Al2O3 based on published models.

A collection of 'shiny' applications for the R package
 'Luminescence'. These mainly, but not exclusively, include applications for
 plotting chronometric data from e.g. luminescence or radiocarbon dating. It
 further provides access to bootstraps tooltip and popover functionality and
 contains the 'jscolor.js' library with a custom 'shiny' output binding.

R implementation of the common parsing tools 'lex' and 'yacc'.

Rasch model and extensions for survey data, using Conditional Maximum likelihood (CML). Carlo Cafiero, Sara Viviani, Mark Nord (2018) <doi:10.1016/j.measurement.2017.10.065>.