This reduced piecewise exponential survival software implements the likelihood ratio test and backward elimination procedure in Han, Schell, and Kim (2012 <doi:10.1080/19466315.2012.698945>, 2014 <doi:10.1002/sim.5915>), and Han et al. (2016 <doi:10.1111/biom.12590>). Inputs to the program can be either times when events/censoring occur or the vectors of total time on test and the number of events. Outputs of the programs are times and the corresponding p-values in the backward elimination. Details about the model and implementation are given in Han et al. 2014. This program can run in R version 3.2.2 and above.

Factor out logic
    and math common to Item Factor Analysis fitting, diagnostics, and
    analysis. It is envisioned as core support code suitable for more
    specialized IRT packages to build upon. Complete access to optimized C
    functions are made available with R_RegisterCCallable().
    This software is described in Pritikin & Falk (2020) <doi:10.1177/0146621620929431>.

Provides a user-friendly interface for managing PostgreSQL
    database connection settings.  The package supplies helper functions to
    create, edit and load connection and option configuration files stored in a
    user-specific directory using the 'odbc' and 'RPostgres' back ends.  These
    helpers make it easy to construct a reproducible connection string from a
    configuration file, either by reading user-defined YAML files or by parsing
    an environment variable.

An enhanced version of the semi-empirical, spatially distributed
    emission and transport model PhosFate implemented in 'R' and 'C++'. It is 
    based on the D-infinity, but also supports the D8 flow method. The currently
    available substances are suspended solids (SS) and particulate phosphorus 
    (PP). A major feature is the allocation of substance loads entering surface 
    waters to their sources of origin, which is a basic requirement for the 
    identification of critical source areas and in consequence a cost-effective
    implementation of mitigation measures. References: Hepp et al. (2022)
    <doi:10.1016/j.jenvman.2022.114514>; Hepp and Zessner (2019)
    <doi:10.3390/w11102161>; Kovacs (2013)
    <http://hdl.handle.net/20.500.12708/9468>.