Negative Binomial (NB) models for two-group comparisons and
    regression inferences from RNA-Sequencing Data.

An implementation of network-based statistics in R using mixed effects models.
    Theoretical background for Network-Based Statistics can be found in Zalesky et al. (2010)
    <doi:10.1016/j.neuroimage.2010.06.041>. For Mixed Effects Models check the
    R package <https://CRAN.R-project.org/package=nlme>.

An interactive document on  the topic of naive Bayes classification  analysis using 'rmarkdown' and 'shiny' packages. Runtime examples are provided in the package function as well as at  <https://kartikeyab.shinyapps.io/NBShiny/>.

Estimates the relative transmission probabilities between cases in an infectious disease outbreak or cluster using naive Bayes. Included are various functions to use these probabilities to estimate transmission parameters such as the generation/serial interval and reproductive number as well as finding the contribution of covariates to the probabilities and visualizing results. The ideal use is for an infectious disease dataset with metadata on the majority of cases but more informative data such as contact tracing or pathogen whole genome sequencing on only a subset of cases. For a detailed description of the methods see Leavitt et al. (2020) <doi:10.1093/ije/dyaa031>.

Performs variable selection in sparse negative binomial GLARMA (Generalised Linear Autoregressive Moving Average) models. For further details we refer the reader to the paper Gomtsyan (2023), <arXiv:2307.00929>.

User-friendly functions for extracting a data
 table (row for each match, column for each group)
 from non-tabular text data using regular expressions,
 and for melting columns that match a regular expression.
 Patterns are defined using a readable syntax
 that makes it easy to build complex patterns
 in terms of simpler, re-usable sub-patterns.
 Named R arguments are translated to column names
 in the output; capture groups without names are used
 internally in order to provide a standard interface
 to three regular expression 'C' libraries
 ('PCRE', 'RE2', 'ICU').
 Output can also include numeric columns via
 user-specified type conversion functions.