Provides a function for fitting Poisson and negative binomial regression models when the number of parameters exceeds the sample size, using the the generalized monotone incremental forward stagewise method.

Provides tools for penalized estimation of flexible hidden Markov models for time series of counts w/o the need to specify a (parametric) family of distributions. These include functions for model fitting, model checking, and state decoding. For details, see Adam, T., Langrock, R., and Weiß, C.H. (2019): Penalized Estimation of Flexible Hidden Markov Models for Time Series of Counts. <arXiv:1901.03275>.

A set of functions for applying a 
    restricted linear algebra to the analysis of 
    count-based data. See the accompanying preprint
    manuscript: "Normalizing need not be the norm:
    count-based math for analyzing single-cell data"
    Church et al (2022) <doi:10.1101/2022.06.01.494334>
    This tool is specifically designed to analyze 
    count matrices from single cell RNA sequencing 
    assays. The tools implement several count-based
    approaches for standard steps in single-cell 
    RNA-seq analysis, including scoring genes and cells, 
    comparing cells and clustering, calculating differential 
    gene expression, and several methods for rank 
    reduction. There are many opportunities for further
    optimization that may prove useful in the analysis of
    other data. We provide the source code freely
    available at <https://github.com/shchurch/countland>
    and encourage users and developers to fork the code for 
    their own purposes.

Provides automated small-cell suppression for one- and two-way 
        frequency tables. Cells falling below a user-defined frequency 
        threshold are masked, with suppression propagated to secondary 
        cells to prevent indirect disclosure. Designed for clinical and 
        health administrative data, the package supports a range of tabular 
        structures and fits into reproducible reporting pipelines, reducing 
        manual review while applying consistent suppression rules across data 
        sharing workflows.