Implements methods for querying data from CalPASS using its API.
 CalPASS Plus.  MMAP API V1. <https://mmap.calpassplus.org/docs/index.html>.

Generates the calibration simplex (a generalization of the reliability diagram) for three-category probability forecasts, as proposed by Wilks (2013) <doi:10.1175/WAF-D-13-00027.1>.

Record and generate a 'gif' of your 'R' sessions plots. When creating 
    a visualization, there is inevitably iteration and refinement that occurs. 
    Automatically save the plots made to a specified directory, previewing them 
    as they would be saved. Then combine all plots generated into a 'gif'
    to show the plot refinement over time.

A tool for causal meta-analysis. This package implements the aggregation formulas and inference methods proposed in Berenfeld et al. (2025) <doi:10.48550/arXiv.2505.20168>. Users can input aggregated data across multiple studies and compute causally meaningful aggregated effects of their choice (risk difference, risk ratio, odds ratio, etc) under user-specified population weighting. The built-in function camea() allows to obtain precise variance estimates for these effects and to compare the latter to a classical meta-analysis aggregate, the random effect model, as implemented in the 'metafor' package <https://CRAN.R-project.org/package=metafor>.

Computes a composite year-on-year index for bank performance
    assessment using the CAMEL framework (Capital Adequacy, Asset Quality,
    Management Efficiency, Earnings, Liquidity). The multivariate
    weighting scheme employs factor analysis with robust covariance
    estimation to derive communality-based weights from the correlation
    matrix of CAMEL ratios.  Provides functions for index computation,
    visualization, and comparison across banks and time periods.The methodology is described in Ayimah et al. (2023a)
    <doi:10.9734/bpi/mono/978-81-19315-32-1> and Ayimah et al. (2023b)
    <https://ajtem.com/index.php/ajtem/article/view/53>.

Implements the board game 'CamelUp' for use in introductory statistics classes using a Shiny app.