Efficient approximation of first passage time densities for diffusion processes based on the First Passage Time Location (FPTL) function.

A collection of functions for calculating Floristic Quality
    Assessment (FQA) metrics using regional FQA databases that have been
    approved or approved with reservations as ecological planning models
    by the U.S. Army Corps of Engineers (USACE). For information on FQA
    see Spyreas (2019) <doi:10.1002/ecs2.2825>. These databases are stored
    in a sister R package, 'fqadata'. Both packages were developed for the
    USACE by the U.S. Army Engineer Research and Development Center’s
    Environmental Laboratory.

Contains regional Floristic Quality Assessment databases that
    have been approved or approved with reservations by the U.S. Army
    Corps of Engineers (USACE). Paired with the 'fqacalc' R package, these
    data sets allow for Floristic Quality Assessment metrics to be
    calculated. For information on FQA see Spyreas (2019)
    <doi:10.1002/ecs2.2825>. Both packages were developed for the USACE by
    the U.S.  Army Engineer Research and Development Center's
    Environmental Laboratory.

Tools for downloading and analyzing floristic quality assessment data. 
  See Freyman et al. (2015) <doi:10.1111/2041-210X.12491> for more information 
  about floristic quality assessment and the associated database.

Comprehensive implementation of advanced ARDL methodologies for 
    cointegration analysis with structural breaks and asymmetric effects.
    Includes: (1) Fourier Quantile ARDL (FQARDL) - quantile regression with 
    Fourier approximation for analyzing relationships across the conditional 
    distribution; (2) Fourier Nonlinear ARDL (FNARDL) - asymmetric cointegration 
    with partial sum decomposition following Shin, Yu & Greenwood-Nimmo (2014) 
    <doi:10.1007/978-1-4899-8008-3_9>; (3) Multi-Threshold NARDL (MTNARDL) - 
    multiple regime asymmetry analysis; (4) Fourier Unit Root Tests - ADF and 
    KPSS tests with Fourier terms following Enders & Lee (2012) 
    <doi:10.1016/j.econlet.2012.05.019> and Becker, Enders & Lee (2006) 
    <doi:10.1111/j.1467-9892.2006.00490.x>. Features automatic lag and frequency 
    selection, PSS bounds testing following Pesaran, Shin & Smith (2001) 
    <doi:10.1002/jae.616>, bootstrap cointegration tests, Wald tests for 
    asymmetry, dynamic multiplier computation, and publication-ready 
    visualizations. Ported from Stata/Python by Dr. Merwan Roudane.