Fast exponentiation when the exponent is an integer.

Density, distribution function, quantile function and random generation for the family of power and reversal power distributions.

Computes power and level tables for goodness-of-fit tests for the normal, Laplace, and uniform distributions. Generates output in 'LaTeX' format to facilitate reporting and reproducibility. Explanatory graphs help visualize the statistical power of test statistics under various alternatives. For more details, see Lafaye De Micheaux and Tran (2016) <doi:10.18637/jss.v069.i03>.

Provides functions for estimating statistical power and required sample sizes 
    in differential abundance microbiome studies using negative binomial models. 
    The methods are based on Agronah and Bolker (2025) <doi:10.1371/journal.pone.0318820>.
    The package includes tools for simulation-based power analysis and sample size 
    estimation using generalized additive models (GAMs), and visualization utilities for exploring 
    the relationship between power, effect size, abundance, and sample size.

Location- and scale-invariant Box-Cox and Yeo-Johnson power transformations
    allow for transforming variables with distributions distant from 0 to
    normality. Transformers are implemented as S4 objects. These allow for
    transforming new instances to normality after optimising fitting parameters
    on other data. A test for central normality allows for rejecting 
    transformations that fail to produce a suitably normal distribution, 
    independent of sample number.

Contains functions to obtain the operational characteristics of 
    bioequivalence studies in Two-Stage Designs (TSD) via simulations.

Power analysis and sample size determination
  for moderation, mediation, and moderated mediation in models
  fitted by structural equation modelling using the 'lavaan'
  package by Rosseel (2012) <doi:10.18637/jss.v048.i02> or
  by multiple regression. The package 'manymome' by
  Cheung and Cheung (2024) <doi:10.3758/s13428-023-02224-z>
  is used to specify the indirect paths or conditional
  indirect paths to be tested.