Package: reinforcedPred
Type: Package
Title: Reinforced Risk Prediction with Budget Constraint
Version: 0.1.1
Authors@R: c(person("Yinghao", "Pan", role = c("aut", "cre"),
                     email = "ypan8@uncc.edu"),
             person("Yingqi", "Zhao", role = "aut"),
             person("Eric", "Laber", role = "aut"))
Author: Yinghao Pan [aut, cre],
  Yingqi Zhao [aut],
  Eric Laber [aut]
Maintainer: Yinghao Pan <ypan8@uncc.edu>
Description: Traditional risk prediction only utilizes baseline factors known 
    to be associated with the disease. Given that longitudinal information are
    routinely measured and documented for patients, it is worthwhile to make
    full use of these data. The available longitudinal biomarker data will 
    likely improve prediction. However, repeated biomarker collection could be 
    costly and inconvenient, and risk prediction for patients at a later time 
    could delay necessary medical decisions. Thus, there is a trade-off between
    high quality prediction and cost. This package implements a cost-effective 
    statistical procedure that recursively incorporates comprehensive 
    longitudinal information into the risk prediction model, taking into 
    account the cost of delaying the decision to a follow-up time when more 
    information is available. The statistical methods are described in the 
    following paper: Pan, Y., Laber, E., Smith, M., Zhao, Y. (2018). Reinforced 
    risk prediction with budget constraint: application to electronic health 
    records data. Manuscript submitted for publication. 
Depends: R (>= 3.5.0)
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Imports: glmnet (>= 2.0-16), MASS (>= 7.3-50), refund (>= 0.1-17),
        stats
RoxygenNote: 6.1.0
URL: https://github.com/Yinghao-Pan/reinforcedPred
BugReports: https://github.com/Yinghao-Pan/reinforcedPred/issues
NeedsCompilation: no
Packaged: 2018-10-31 00:43:17 UTC; yinghaopan
Repository: CRAN
Date/Publication: 2018-10-31 10:20:11 UTC
Built: R 3.5.3; ; 2020-04-22 09:11:34 UTC; windows
