Dynamic treatment regime estimation and inference via G-estimation, 
  dynamic weighted ordinary least squares (dWOLS) and Q-learning. Inference via 
  bootstrap and recursive sandwich estimation. Estimation and 
  inference for survival outcomes via Dynamic Weighted Survival Modeling (DWSurv). 
  Extension to continuous treatment variables. Wallace et al. (2017) 
  <DOI:10.18637/jss.v080.i02>; Simoneau et al. (2020) 
  <DOI:10.1080/00949655.2020.1793341>.

Provides methods for estimating multi-stage optimal 
    dynamic treatment regimes for survival outcomes with dependent censoring.
    Cho, H., Holloway, S. T., and Kosorok, M. R. (2022) <doi:10.1093/biomet/asac047>.

Methods for evaluating the probability mass function, cumulative distribution function, and generating random samples from discrete tempered stable distributions. For more details see Grabchak (2021) <doi:10.1007/s11009-021-09904-3>.

It is a novel tool used to identify the candidate drugs against a particular disease based on the drug target set enrichment analysis. It assumes the most effective drugs are those with a closer affinity in the protein-protein interaction network to the specified disease. (See Gómez-Carballa et al. (2022) <doi: 10.1016/j.envres.2022.112890> and Feng et al. (2022) <doi: 10.7150/ijms.67815> for disease expression profiles; see Wishart et al. (2018) <doi: 10.1093/nar/gkx1037> and Gaulton et al. (2017) <doi: 10.1093/nar/gkw1074> for drug target information; see Kanehisa et al. (2021) <doi: 10.1093/nar/gkaa970> for the details of KEGG database.)

Basic time series functionalities such as listing of missing
    values, application of arbitrary aggregation as well as rolling (asymmetric)
    window functions and automatic detection of periodicity. As it is mainly
    based on 'data.table', it is fast and (in combination with the 'R6' package)
    offers reference semantics. In addition to its native R6 interface, it
    provides an S3 interface for those who prefer the latter. Finally yet
    importantly, its functional approach allows for incorporating
    functionalities from many other packages.