Provides tools for the statistical analysis of regular vine copula 
    models, see Aas et al. (2009) <doi:10.1016/j.insmatheco.2007.02.001> and 
    Dissman et al. (2013) <doi:10.1016/j.csda.2012.08.010>.
    The package includes tools for parameter estimation, model selection,
    simulation, goodness-of-fit tests, and visualization. Tools for estimation,
    selection and exploratory data analysis of bivariate copula models are also
    provided.

Implements D-vine quantile regression models with
  parametric or nonparametric pair-copulas. See 
  Kraus and Czado (2017) <doi:10.1016/j.csda.2016.12.009> and
  Schallhorn et al. (2017) <doi:10.48550/arXiv.1705.08310>.

Produces violin plots with optional nonparametric (Mann-Whitney test) and parametric (Tukey's honest significant difference) mean comparison and linear regression. This package aims to be a simple and quick visualization tool for comparing means and assessing trends of categorical factors.

A violin plot is a combination of a box plot and a kernel density plot. This package allows extensive customisation of violin plots.

Generate a violin point plot, a combination of a violin/histogram
    plot and a scatter plot by offsetting points within a category based on their
    density using quasirandom noise.

Provides tools for designing virus protein panels through sequence clustering and protein sequence analysis. The package includes functionality for filtering sequences, removing redundancy, identifying outliers, clustering sequences, and calculating entropy to evaluate clustering quality. A publication describing these methods is in preparation and will be added once available.

Implements an entropy-informed pipeline for detecting
    emerging variants in viral amino acid sequence data, extending
    prior clustering-based approaches including hemagglutinin
    clustering methods (Li et al., 2015)
    <doi:10.1142/9789814667944_0018>. Provides a fully vectorized
    FASTA preprocessing toolkit covering header parsing, two-pass
    date and country extraction, ambiguous-residue filtering, and
    integer encoding under a 25-symbol amino acid alphabet. Computes
    per-site Shannon entropy across user-defined cumulative,
    sliding, or disjoint temporal partitions and clusters per-site
    entropy values using Gaussian mixture models via 'mclust'
    (Scrucca et al., 2016) <doi:10.32614/RJ-2016-021>. Quantifies
    temporal distributional shifts between partitions using the
    Hellinger distance (van der Vaart, 1998)
    <doi:10.1017/CBO9780511802256>, and detects temporal change
    points non-parametrically using energy statistics (Matteson and
    James, 2014) <doi:10.1080/01621459.2013.849605> via 'ecp' or
    wild binary segmentation (Fryzlewicz, 2014)
    <doi:10.1214/14-AOS1245> via 'HDcpDetect'. Per-site amino-acid 
    frequency tables and entropy trajectory plots characterize sequence 
    composition and evolutionary dynamics across time. A configurable 
    multi-variant simulation engine generates synthetic sequence 
    time series with known ground truth for benchmarking detection pipelines. 
    A curated dataset of SARS-CoV-2 Variants of Concern and Variants of
    Interest with associated lineage and surveillance metadata is
    included, along with a bundled National Center for Biotechnology
    Information (NCBI) Spike protein sample and vignettes
    demonstrating the full workflow.