A suite of likelihood ratio test based methods to use in pharmacovigilance. Contains various testing and post-processing functions.

The pipeline contained in this package provides tools used in the
    Solar Durability and Lifetime Extension Center (SDLE) for the analysis of
    Performance Loss Rates (PLR) in real world photovoltaic systems. Functions
    included allow for data cleaning, feature correction, power predictive modeling, 
    PLR determination, and uncertainty bootstrapping through various methods 
    <doi:10.1109/PVSC40753.2019.8980928>.
    The vignette "Pipeline Walkthrough" gives
    an explicit run through of typical package usage. 
    This material is based upon work supported by the U.S Department
    of Energy's Office of Energy Efficiency and Renewable Energy (EERE) under
    Solar Energy Technologies Office (SETO) Agreement Number DE-EE-0008172. 
    This work made use of the High Performance Computing Resource in the 
    Core Facility for Advanced Research Computing at
    Case Western Reserve University.

Estimates (and controls for) phylogenetic signal through phylogenetic eigenvectors regression (PVR) and phylogenetic signal-representation (PSR) curve, along with some plot utilities.

Calculates various functions needed for design and monitoring survival trials
    accounting for complex situations such as delayed treatment effect, treatment crossover, non-uniform accrual,
    and different censoring distributions between groups. The event time distribution is assumed to be
    piecewise exponential (PWE) distribution and the entry time is assumed to be piecewise uniform distribution.
    As compared with Version 1.2.1, two more types of hybrid crossover are added. 
    A bug is corrected in the function "pwecx" that calculates the crossover-adjusted survival, distribution, 
    density, hazard and cumulative hazard functions. 
    Also, to generate the crossover-adjusted event time random variable,  a more efficient 
    algorithm is used and the output includes crossover indicators.