Contains functions for the analysis of Discrete Time Hidden Markov Models, Markov Modulated GLMs and the Markov Modulated Poisson Process. It includes functions for simulation, parameter estimation, and the Viterbi algorithm. See the topic "HiddenMarkov" for an introduction to the package, and "Change Log" for a list of recent changes. The algorithms are based of those of Walter Zucchini.

Generates HIDECAN plots that summarise and combine 
  the results of genome-wide association studies (GWAS) and transcriptomics 
  differential expression analyses (DE), along with manually curated candidate genes of interest. The HIDECAN plot 
  is presented in Angelin-Bonnet et al. (2023) (currently in review).

Performs linear discriminant analysis in high dimensional
        problems based on reliable covariance estimators for problems
        with (many) more variables than observations. Includes routines
        for classifier training, prediction, cross-validation and
        variable selection.

Calculate clinical scores for hidradenitis suppurativa (HS), a
  dermatologic disease.  The scores are typically used for evaluation of
  efficacy in clinical trials.  The scores are not commonly used in clinical
  practice.  The specific scores implemented are Hidradenitis Suppurativa 
  Clinical Response (HiSCR) (Kimball, et al. (2015) <doi:10.1111/jdv.13216>),
  Hidradenitis Suppurativa Area and Severity Index Revised (HASI-R) (Goldfarb,
  et al. (2020) <doi:10.1111/bjd.19565>), hidradenitis suppurativa Physician
  Global Assessment (HS PGA) (Marzano, et al. (2020) <doi:10.1111/jdv.16328>),
  and the International Hidradenitis Suppurativa Severity Score System (IHS4)
  (Zouboulis, et al. (2017) <doi:10.1111/bjd.15748>).

Pure set data visualization approaches are often limited in
    scalability due to the combinatorial explosion of distinct set families as
    the number of sets under investigation increases. hierarchicalSets applies
    a set centric hierarchical clustering of the sets under investigation and
    uses this hierarchy as a basis for a range of scalable visual
    representations. hierarchicalSets is especially well suited for collections
    of sets that describe comparable comparable entities as it relies on the
    sets to have a meaningful relational structure.