Calculates relevance and significance values for
  simple models and for many types of regression models.
  These are introduced in
  'Stahel, Werner A.' (2021)
  "Measuring Significance and Relevance instead of p-values."
  <https://stat.ethz.ch/~stahel/relevance/stahel-relevance2103.pdf>.
  These notions are also applied to replication studies,
  as described in the manuscript
  'Stahel, Werner A.' (2022)
  "'Replicability': Terminology, Measuring Success, and Strategy"
  available in the documentation.

Tools to fit and simulate realizations from relational event models.

Checking the reliability of predictions via the CORP approach,
    which generates provably statistically 'C'onsistent, 'O'ptimally binned, and
    'R'eproducible reliability diagrams using the 'P'ool-adjacent-violators
    algorithm. See Dimitriadis, Gneiting, Jordan (2021) <doi:10.1073/pnas.2016191118>.

Perform structural reliability analysis, including computation and
    simulation with system signatures, Samaniego (2007)
    <doi:10.1007/978-0-387-71797-5>, and survival signatures, Coolen and
    Coolen-Maturi (2013) <doi:10.1007/978-3-642-30662-4_8>. Additionally
    supports parametric and topological inference given system lifetime data,
    Aslett (2012) <https://www.louisaslett.com/PhD_Thesis.pdf>.

Calculates and compares various reliability coefficients for 
    unidimensional and multidimensional scales. Supported unidimensional 
    estimators include coefficient alpha, congeneric reliability, the 
    Gilmer-Feldt coefficient, Feldt's classical congeneric reliability, 
    Hancock's H, Heise-Bohrnstedt's omega, Kaiser-Caffrey's alpha, and Ten 
    Berge and Zegers' mu series. Multidimensional estimators include 
    stratified alpha, maximal reliability, correlated factors reliability, 
    second-order factor reliability, and bifactor reliability.
    See Cho (2021) <doi:10.1007/s11336-021-09801-1>,
    Cho (2024) <doi:10.1037/met0000475>,
    Cho (2025) <doi:10.1037/met0000525>.

Modeling and plotting functions for Reliability Growth Analysis (RGA) and Non-Homogeneous Poisson Process (NHPP) models for repairable systems. RGA models include the Duane (1962) <doi:10.1109/TA.1964.4319640>, NHPP by Crow (1975) (No. AMSAATR138), Piecewise Weibull NHPP by Guo et al. (2010) <doi:10.1109/RAMS.2010.5448029>, and Piecewise Weibull NHPP with Change Point Detection based on the 'segmented' package by Muggeo (2024) <https://cran.r-project.org/package=segmented>. Repairable systems functions include the Mean Cumulative Function (MCF) using the Nelson-Aalen estimator, parametric Power Law and Log-Linear NHPP models, and forecasting.