Generate Mermaid syntax for a pedigree flowchart from a pedigree data frame.
    Mermaid syntax is commonly used to generate plots, charts, diagrams, and flowcharts. It is a textual syntax for creating reproducible illustrations. This package generates Mermaid syntax from a pedigree data frame to visualize a pedigree flowchart. The Mermaid syntax can be embedded in a Markdown or R Markdown file, or viewed on Mermaid editors and renderers. Links' shape, style, and orientation can be customized via function arguments, and nodes' shapes and styles can be customized via optional columns in the pedigree data frame.

Provides functions to estimate mixed probit models using, for 
    instance, pedigree data like in <doi:10.1002/sim.1603>. The models are also 
    commonly called liability threshold models. The approximation is 
    based on direct log marginal likelihood approximations like the randomized 
    Quasi-Monte Carlo suggested by <doi:10.1198/106186002394> with a similar 
    procedure to approximate the derivatives. The minimax tilting method 
    suggested by <doi:10.1111/rssb.12162> is also supported. Graph-based methods 
    are also provided that can be used to simplify pedigrees.

A collection of functions for modelling mutations in
    pedigrees with marker data, as used e.g. in likelihood computations
    with microsatellite data. Implemented models include equal,
    proportional and stepwise models, as well as random models for
    experimental work, and custom models allowing the user to apply any
    valid mutation matrix. Allele lumping is done following the
    lumpability criteria of Kemeny and Snell (1976), ISBN:0387901922.

An R implementation of methods employed in the field of pedometrics, soil science
    discipline dedicated to studying the spatial, temporal, and spatio-temporal variation of soil
    using statistical and computational methods. The methods found here include the calibration of
    linear regression models using covariate selection strategies, computation of summary validation
    statistics for predictions, generation of summary plots, evaluation of the local quality of a
    geostatistical model of uncertainty, and so on. Other functions simply extend the
    functionalities of or facilitate the usage of functions from other packages that are commonly
    used for the analysis of soil data. Formerly available versions of suggested packages no longer
    available from CRAN can be obtained from the CRAN archive
    <https://cran.r-project.org/src/contrib/Archive/>.