A matrix of agreement patterns and counts for record pairs is the input for the procedure.  An EM algorithm is used to impute plausible values for missing record pairs.  A second EM algorithm, incorporating possible correlations between per-field agreement, is used to estimate posterior probabilities that each pair is a true match - i.e. constitutes the same individual.

In metabolic flux experiments tracer molecules (often glucose
    containing labelled carbon) are incorporated in compounds measured
    using mass spectrometry. The mass isotopologue distributions of these
    compounds needs to be corrected for natural abundance of labelled
    carbon and other effects, which are specific on the compound and
    ionization technique applied. This package provides functions to
    correct such effects in gas chromatography atmospheric pressure
    chemical ionization mass spectrometry analyses.

Statistical modeling for correlated count data using the beta-binomial distribution, described in Martin et al. (2020) <doi:10.1214/19-AOAS1283>. It allows for both mean and overdispersion covariates.

Implements lasso and ridge regression for dichotomised outcomes (<doi:10.1080/02664763.2023.2233057>), i.e., numerical outcomes that were transformed to binary outcomes. Such artificial binary outcomes indicate whether an underlying measurement is greater than a threshold.

Provides 'coroutines' for R, a family of functions that can
    be suspended and resumed later on. This includes 'async' functions
    (which await) and generators (which yield). 'Async' functions are
    based on the concurrency framework of the 'promises' package.
    Generators are based on a dependency free iteration protocol defined
    in 'coro' and are compatible with iterators from the 'reticulate'
    package.

Contains an implementation of a confounding robust independent component analysis (ICA) for noisy and grouped data. The main function coroICA() performs a blind source separation, by maximizing an independence across sources and allows to adjust for varying confounding based on user-specified groups. Additionally, the package contains the function uwedge() which can be used to approximately jointly diagonalize a list of matrices. For more details see the project website <https://sweichwald.de/coroICA/>.