Provides an implementation of simultaneous tolerance bounds (STB), useful for checking whether a numeric vector fits to a hypothetical null-distribution or not.
             Furthermore, there are functions for computing STB (bands, intervals) for random variates of linear mixed models fitted with package 'VCA'. All kinds of, possibly transformed 
             (studentized, standardized, Pearson-type transformed) random variates (residuals, random effects), can be assessed employing STB-methodology.

A set of consistent, opinionated functions to quickly check
    function arguments, coerce them to the desired configuration, or
    deliver informative error messages when that is not possible.

Spatio-temporal change of support (STCOS) methods are designed for statistical inference
	on geographic and time domains which differ from those on which the data were observed. In
	particular, a parsimonious class of STCOS models supporting Gaussian outcomes was introduced
	by Bradley, Wikle, and Holan <doi:10.1002/sta4.94>. The 'stcos' package contains tools which
	facilitate use of STCOS models.

Estimates a covariance matrix using Stein's isotonized covariance
    estimator, or a related estimator suggested by Haff.

Algorithms of nonparametric sequential test and online 
  change-point detection for streams of univariate (sub-)Gaussian, binary, 
  and bounded random variables, introduced in following publications -
  Shin et al. (2024) <doi:10.48550/arXiv.2203.03532>,
  Shin et al. (2021) <doi:10.48550/arXiv.2010.08082>.

Contains three main functions including
  stddiff.numeric(), stddiff.binary() and stddiff.category().
  These are used to calculate the standardized difference between two groups.
  It is especially used to evaluate the balance between two groups
  before and after propensity score matching.

Functions for computing a standardized moderation effect
             in moderated regression and forming its confidence interval
             by nonparametric bootstrapping as proposed in
             Cheung, Cheung, Lau, Hui, and Vong (2022)
             <doi:10.1037/hea0001188>. Also includes simple-to-use
             functions for computing conditional effects (unstandardized
             or standardized) and plotting moderation effects.