Enable researchers to adjust identification rates using the 1/(lineup size) method, generate the full receiver operating characteristic (ROC) curves, and statistically compare the area under the curves (AUC). 
  References: Yueran Yang & Andrew Smith. (2020). "fullROC: An R package for generating and analyzing eyewitness-lineup ROC curves". <doi:10.13140/RG.2.2.20415.94885/1>  ,
              Andrew Smith, Yueran Yang, & Gary Wells. (2020). "Distinguishing between investigator discriminability and eyewitness discriminability: A method for creating full receiver operating characteristic curves of lineup identification performance". Perspectives on Psychological Science, 15(3), 589-607. <doi:10.1177/1745691620902426>.

A collection of R games and other funny stuff, such as the
    classic Mine sweeper and sliding puzzles.

Helps users with analyses in functional biogeography by loading 
    and combining data, computing trait coverage, as well as computing 
    functional diversity indices, drawing maps, correlating them with the 
    environment, and upscaling assemblages.

Provides methods to compute simultaneous prediction and confidence
    bands for dense time series data. The implementation builds on the
    functional bootstrap approach proposed by Lenhoff et al. (1999)
    <doi:10.1016/S0966-6362(98)00043-5> and extended by Koska et al. (2023)
    <doi:10.1016/j.jbiomech.2023.111506> to support both independent and
    clustered (hierarchical) data. Includes a simple API (see band()) and an
    'Rcpp' backend for performance.

Provides functions to have visualization and clean-up of enriched gene ontologies (GO) terms, 
    protein complexes and pathways (obtained from multiple databases) using 'ConsensusPathDB' 
    from gene set over-expression analysis. Performs clustering of pathway based on similarity 
    of over-expressed gene sets and visualizations similar to Ingenuity Pathway Analysis (IPA) 
    when up and down regulated genes are known. The methods are described in a paper currently
    submitted by Orecchioni et al, 2020 in Nanoscale.