Weighted-L2 FPOP Maidstone et al. (2017) <doi:10.1007/s11222-016-9636-3> and pDPA/FPSN Rigaill (2010) <arXiv:1004.0887> algorithm for detecting multiple changepoints in the mean of a vector. Also includes a few model selection functions using Lebarbier (2005) <doi:10.1016/j.sigpro.2004.11.012> and the 'capsushe' package.

A collection of functions to optimize portfolios and to analyze them from different points of view.

Returns the noncentrality parameter of the noncentral F
        distribution if probability of type I and type II error, degrees
        of freedom of the numerator and the denominator are given.  It
        may be useful for computing minimal detectable differences for
        general ANOVA models.  This program is documented in the paper
        of A. Baharev, S. Kemeny, On the computation of the noncentral
        F and noncentral beta distribution; Statistics and Computing,
        2008, 18 (3), 333-340.

All data sets required for the examples and exercises
  in the book "Forecasting: principles and practice" (2nd ed, 2018)
  by Rob J Hyndman and George Athanasopoulos <https://otexts.com/fpp2/>.
  All packages required to run the examples are also loaded.

All data sets required for the examples and exercises in the book
    "Forecasting: principles and practice" by Rob J Hyndman and George Athanasopoulos
    <https://OTexts.com/fpp3/>. All packages required to run the examples are also
    loaded. Additional data sets not used in the book are also included.

Provides optimized 'C++' code for computing the partial Receiver Operating Characteristic (ROC) test used in niche and species distribution modeling. The implementation follows Peterson et al. (2008) <doi:10.1016/j.ecolmodel.2007.11.008>. Parallelization via 'OpenMP' was implemented with assistance from the 'DeepSeek' Artificial Intelligence Assistant (<https://www.deepseek.com/>).

Provides functions for calculating various measures of foreign 
    policy similarity or association commonly used in the study of international 
    relations. These include Signorino and Ritter's S statistic (weighted and 
    unweighted), Benati and Capurri's chance-corrected S statistic (A), Cohen's 
    weighted kappa, Scott's pi, and Kendall's tau-b. The package facilitates 
    the generation of dyadic similarity scores for empirical analyses and can 
    also serve as an educational resource for understanding how such measures 
    are calculated.