Provides functions for fitting various penalized parametric and semi-parametric mixture cure models with different penalty functions, testing for a significant cure fraction, and testing for sufficient follow-up as described in Fu et al (2022)<doi:10.1002/sim.9513> and Archer et al (2024)<doi:10.1186/s13045-024-01553-6>. False discovery rate controlled variable selection is provided using model-X knock-offs.

A procedure that fits derivative curves based on a sequence of quotient differences.  In a hierarchical setting the package produces estimates of subject-specific and group-specific derivative curves.  In a non-hierarchical setting the package produces a single derivative curve.

Hard drive data: Class of data allowing the easy importation/manipulation of out of memory data sets. The data sets are located on disk but look like in-memory, the syntax for manipulation is similar to 'data.table'. Operations are performed "chunk-wise" behind the scene. See <https://lrberge.github.io/hdd/> for more information.

Provides a self-contained, static build of the 'HDF5'
    (Hierarchical Data Format 5) 'C' library (release 2.1.1) for R
    package developers. Designed for use in the 'LinkingTo' field,
    it enables zero-dependency integration by building the library
    entirely from source during installation. Additionally, it compiles
    and internally links a comprehensive suite of advanced compression
    filters and their 'HDF5' plugins (Zstd, LZ4, Blosc/Blosc2, Snappy,
    ZFP, Bzip2, LZF, Bitshuffle, szip, and gzip). These plugins are
    integrated out-of-the-box, allowing downstream packages to utilize
    high-performance compression directly through the standard 'HDF5'
    API while keeping the underlying third-party headers fully
    encapsulated. 'HDF5' is developed by The HDF Group
    <https://www.hdfgroup.org/>.

'HDF5' is a data model, library and file format for storing
    and managing large amounts of data. This package provides a nearly
    feature complete, object oriented  wrapper for the 'HDF5' API
    <https://support.hdfgroup.org/documentation/hdf5/latest/_r_m.html> using R6 classes.
    Additionally, functionality is added so that 'HDF5' objects behave very
    similar to their corresponding R counterparts.