Analyze differences among time series curves with p-value
        adjustment for multiple comparisons introduced in Oleson et al
        (2015) <DOI:10.1177/0962280215607411>.

Tools and workflow to choose design parameters in Bayesian adaptive single-arm phase II trial designs with binary endpoint (response, success) with possible stopping for efficacy and futility at interim analyses. Also contains routines to determine and visualize operating characteristics. See Kopp-Schneider et al. (2018) <doi:10.1002/bimj.201700209>.

Provide a tool to easily build customized data flows to pre-process large volumes 
    of information from different sources. To this end, 'bdpar' allows to (i) easily use and 
    create new functionalities and (ii) develop new data source extractors according to the 
    user needs. Additionally, the package provides by default a predefined data flow 
    to extract and pre-process the most relevant information (tokens, dates, ... ) from some textual 
    sources (SMS, Email, YouTube comments).

Computation of asymptotic confidence intervals for negative and positive predictive values in binary diagnostic tests in case-control studies. Experimental design for hypothesis tests on predictive values.

Fits a discharge rating curve based on the power-law and the generalized power-law from data on paired stage and discharge measurements in a given river using a Bayesian hierarchical model as described in Hrafnkelsson et al. (2020) <arXiv:2010.04769>.

Implements Bayesian inference to detect signal from blinded 
    clinical trial when total number of adverse events of special 
    concerns and total risk exposures from all patients are available in the study.  
    For more details see the article by Mukhopadhyay et. al. (2018) 
    titled 'Bayesian Detection of Potential Risk Using Inference on Blinded Safety Data', 
    in Pharmaceutical Statistics (to appear).

Provides a continuous date scale, omitting weekends and holidays.

This is a special case of sparse matrices, used by coxme.