Computes exact conditional p-values and quantiles using an
 implementation of the Shift-Algorithm by Streitberg & Roehmel.

Provides fast dynamic-programming algorithms in 'C++'/'Rcpp'
    (with pure 'R' fallbacks) for the exact finite-sample distributions
    and p-values of Christoffersen (1998) independence (IND) and
    conditional-coverage (CC) VaR backtests. For completeness, it also
    provides the exact unconditional-coverage (UC) test following
    Kupiec (1995) via a closed-form binomial enumeration. See
    Christoffersen (1998) <doi:10.2307/2527341> and Kupiec (1995)
    <doi:10.3905/jod.1995.407942>.

Implements comprehensive test data engineering methods as described in 
    Shojima (2022, ISBN:978-9811699856). Provides statistical techniques for 
    engineering and processing test data: Classical Test Theory (CTT) with 
    reliability coefficients for continuous ability assessment; Item Response 
    Theory (IRT) including Rasch, 2PL, and 3PL models with item/test information 
    functions; Latent Class Analysis (LCA) for nominal clustering; Latent Rank 
    Analysis (LRA) for ordinal clustering with automatic determination of cluster 
    numbers; Biclustering methods including infinite relational models for 
    simultaneous clustering of examinees and items without predefined cluster 
    numbers; and Bayesian Network Models (BNM) for visualizing inter-item 
    dependencies. Features local dependence analysis through LRA and biclustering, 
    parameter estimation, dimensionality assessment, and network structure 
    visualization for educational, psychological, and social science research.

A 'Shiny'-based toolkit for item/test analysis. It is designed for multiple-choice, true-false, and open-ended questions. The toolkit is usable with datasets in 1-0 or other formats. Key analyses include difficulty, discrimination, response-option analysis, reports. The classical test theory methods used are described in Ebel & Frisbie (1991, ISBN:978-0132892314).