Suite of functions to study animal incubation.
    At the core of incR 
    lies an algorithm that allows for the scoring of 
    incubation behaviour. Additionally, several functions 
    extract biologically relevant metrics of incubation such as off-bout number 
    and off-bout duration - for a review of avian incubation studies, 
    see Nests, Eggs, and Incubation: New ideas about avian reproduction (2015) 
    edited by D. Charles Deeming and S. James Reynolds <doi:10.1093/acprof:oso/9780198718666.001.0001>.

Tools for estimating incidence from biomarker data in cross-
    sectional surveys, and for calibrating tests for recent infection. 
    Implements and extends the method of Kassanjee et al. (2012)
    <doi:10.1097/EDE.0b013e3182576c07>.

Fit parametric models for time-to-event data that show an initial
    'incubation period', i.e. a variable delay phase where no events occur.
    The delayed Weibull distribution serves as the foundational data model.
    For parameter estimation, different flavours of maximum likelihood
    estimation ('MLE') and the method of maximum product of spacings estimation
    ('MPSE') are implemented. Bootstrap confidence intervals for parameters and
    significance tests in a two group setting are provided.

Implements Inductive Node-Splitting Cross-Validation (INCV) for
    selecting the number of communities in stochastic block models. Provides
    f-fold and random-split node-level cross-validation, along with
    competing methods including CROISSANT, Edge Cross-Validation (ECV), and
    Node Cross-Validation (NCV). Supports both SBM and Degree-Corrected
    Block Models (DCBM), with multiple loss functions (L2, binomial
    deviance, AUC). Includes network simulation utilities for SBM, RDPG,
    and latent space models.

A 'shiny' app that supports both dual and bulk RNA-seq, with the dual
    RNA-seq functionality offering the flexibility to perform either a
    sequential approach (where reads are mapped separately to each genome)
    or a combined approach (where reads are aligned to a single merged
    genome). The user-friendly interface automates the analysis process,
    providing step-by-step guidance, making it easy for users to navigate
    between different analysis steps, and download intermediate results
    and publication-ready plots.