Provides standardized access to a range of re-scaling methods for numerical vectors
    and time-series features calculated within the 'theft' ecosystem.

A toolkit for assessing data normality using a comprehensive collection of statistical methods. 
    It includes descriptive measures and formal hypothesis tests, such as skewness and kurtosis tests, 
    the Anderson–Darling test, the Shapiro–Wilk test, and the D'Agostino–Pearson K2 omnibus test.

Package including an interactive Shiny application for
    testing normality visually.

Provides simple methods for centering and scaling of numeric data. 
    Columns or rows can be ignored when normalizing or be normalized jointly.

Normalize a given Hadamard matrix. A Hadamard matrix is said to be normalized when its first row and first column entries are all 1, see Hedayat, A. and Wallis, W. D. (1978) "Hadamard matrices and their applications. The Annals of Statistics, 1184-1238." <doi:10.1214/aos/1176344370>.

Functions for the normal Laplace distribution.  Currently, it
 provides limited functionality.  Density, distribution and quantile
 functions, random number generation, and moments are provided.

A collection of utilities referred to Exponential Power distribution, also known as General Error Distribution (see Mineo, A.M. and Ruggieri, M. (2005), A software Tool for the Exponential Power Distribution: The normalp package. In Journal of Statistical Software, Vol. 12, Issue 4).

Normative data are often used to estimate the relative position of a raw test score in the population. This package allows for deriving regression-based normative data. It includes functions that enable the fitting of regression models for the mean and residual (or variance) structures, test the model assumptions, derive the normative data in the form of normative tables or automatic scoring sheets, and estimate confidence intervals for the norms. This package accompanies the book Van der Elst, W. (2024). Regression-based normative data for psychological assessment. A hands-on approach using R. Springer Nature.