Cleans and Normalizes FLUOstar DBF and DAT Files obtained from liposome flux assays. Users should verify extended usage of the package on files from other assay types.

Multivariate Normal (i.e. Gaussian) Mixture Models (S3) Classes.
    Fitting models to data using 'MLE' (maximum likelihood estimation) for
    multivariate normal mixtures via smart parametrization using the 'LDL'
    (Cholesky) decomposition, see McLachlan and Peel (2000, ISBN:9780471006268),
    Celeux and Govaert (1995) <doi:10.1016/0031-3203(94)00125-6>.

Functions for normalizing psychometric test scores. The normalization aims at correcting the metrological properties of the psychometric tests such as the ceiling and floor effects and the curvilinearity (unequal interval scaling). Functions to compute and plot predictions in the natural scale of the psychometric test from the estimates of a linear mixed model estimated on the normalized scores are also provided. See Philipps et al (2014) <doi:10.1159/000365637> for details.

A toolbox for calculating continuous norms for psychological tests, where the norms can be age-dependent. The norms are based Generalized Additive Models for Location, Scale, and Shape (GAMLSS) for the test scores in the normative sample. The package includes functions for model selection, reliability estimation, and calculating norms, including confidence intervals. For more details, see Timmerman et al. (2021) <doi:10.1037/met0000348>.

Allele frequency databases for 50 forensic short tandem
    repeat (STR) markers, covering Norway and several broader regional
    populations: Europe, Africa, South America, West Asia, Middle Asia,
    and East Asia. Developed and maintained for use at the Department of
    Forensic Sciences, Oslo, Norway.

Five omnibus tests for testing the composite hypothesis of
        normality.

Tests the goodness-of-fit to the Normal distribution for the errors of an ARMA model.

Despite that several tests for normality in stationary processes have been proposed in the literature, consistent implementations of these tests in programming languages are limited. Seven normality test are implemented. The asymptotic Lobato & Velasco's, asymptotic Epps, Psaradakis and  Vávra, Lobato & Velasco's and Epps sieve bootstrap approximations, El bouch et al., and the random projections tests for univariate stationary process. Some other diagnostics such as, unit root test for  stationarity, seasonal tests for seasonality, and arch effect test for volatility; are also performed. Additionally, the El bouch test performs normality tests for bivariate time series. The package also offers residual diagnostic for linear time series models developed in several packages.