Performs drug demand forecasting by modeling drug dispensing data while taking into account predicted enrollment and treatment discontinuation dates. The gap time between randomization and the first drug dispensing visit is modeled using intervalcensored exponential, Weibull, loglogistic, or lognormal distributions (AndersonBergman (2017) <doi:10.18637/jss.v081.i12>). The number of skipped visits is modeled using Poisson, zeroinflated Poisson, or negative binomial distributions (Zeileis, Kleiber & Jackman (2008) <doi:10.18637/jss.v027.i08>). The gap time between two consecutive drug dispensing visits given the number of skipped visits is modeled using linear regression based on least squares or least absolute deviations (Birkes & Dodge (1993, ISBN:0471568813)). The number of dispensed doses is modeled using linear or linear mixedeffects models (McCulloch & Searle (2001, ISBN:047119364X)).
Package details 


Author  Kaifeng Lu [aut, cre] (<https://orcid.org/0000000261607119>) 
Maintainer  Kaifeng Lu <kaifenglu@gmail.com> 
License  GPL (>= 2) 
Version  0.1.3 
Package repository  View on CRAN 
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