Provides an algorithm for creating mandalas. From the perspective of classic mathematical curves and rigid movements on the plane, the package allows you to select curves and produce mandalas from the curve. The algorithm was developed based on the book by Alcoforado et. al. entitled "Art, Geometry and Mandalas with R" (2022) in press by the USP Open Books Portal.

Estimates membership for the Mandelbrot set.

Mixture model with overlapping clusters for binary actor-event data. Parameters are estimated in a Bayesian framework. Model and inference are described in Ranciati, Vinciotti, Wit (2017) Modelling actor-event network data via a mixture model under overlapping clusters. Submitted.

Methods for performing genetic risk
        prediction from genotype data.  You can use it to perform risk
        prediction for individuals, or for families with missing data.

Create interactive manhattan, Q-Q and volcano plots that are usable from the R console, 
    in 'Dash' apps, in the 'RStudio' viewer pane, in 'R Markdown' documents, and in 'Shiny' apps.
    Hover the mouse pointer over a point to show details or drag a rectangle to
    zoom. A manhattan plot is a popular graphical method for visualizing results
    from high-dimensional data analysis such as a (epi)genome wide association study
    (GWAS or EWAS), in which p-values, Z-scores, test statistics are plotted on a scatter
    plot against their genomic position. Manhattan plots are used for visualizing
    potential regions of interest in the genome that are associated with a phenotype.
    Interactive manhattan plots allow the inspection of specific value (e.g. rs number or
    gene name) by hovering the mouse over a cell, as well as zooming into a region of the
    genome (e.g. a chromosome) by dragging a rectangle around the relevant area.
    This work is based on the 'qqman' package and the 'plotly.js'
    engine. It produces similar manhattan and Q-Q plots as the 'manhattan' and 'qq'
    functions in the 'qqman' package, with the advantage of including extra annotation 
    information and interactive web-based visualizations directly from R. 
    Once uploaded to a 'plotly' account, 'plotly' graphs (and the data behind them) 
    can be viewed and modified in a web browser.