Simulating and estimating peer effect models and network formation models. The class of peer effect models includes linear-in-means models (Lee, 2004; <doi:10.1111/j.1468-0262.2004.00558.x>), Tobit models (Xu and Lee, 2015; <doi:10.1016/j.jeconom.2015.05.004>), and discrete numerical data models (Houndetoungan, 2025; <doi:10.48550/arXiv.2405.17290>). The network formation models include pair-wise regressions with degree heterogeneity (Graham, 2017; <doi:10.3982/ECTA12679>) and exponential random graph models (Mele, 2017; <doi:10.3982/ECTA10400>).

Calculation of sex- and age-standardized growth metrics 
    based on the 2000 CDC growth charts for children and adolescents 
    with ages of >= 24.0 to < 240 months. Provides functions to generate 
    z-scores and percentiles for weight, height, and body mass index (BMI) 
    using the LMS method (lambda-mu-sigma). Includes extended BMI z-scores 
    for values above the 95th percentile to more accurately characterize 
    the sex- and age-standardized BMI of children with very high BMIs.

A session-based engine for cognitive diagnostic computerized
    adaptive testing (CD-CAT), the application of adaptive testing to
    cognitive diagnosis models. Three models are supported: the deterministic
    inputs, noisy "and" gate (DINA), the deterministic inputs, noisy "or"
    gate (DINO), and the generalized DINA (GDINA) model. Item selection
    criteria include Kullback-Leibler (KL) information, posterior-weighted
    Kullback-Leibler (PWKL), modified posterior-weighted Kullback-Leibler
    (MPWKL), and Shannon entropy (SHE). Latent attribute profiles are
    estimated by maximum likelihood estimation (MLE), maximum a posteriori
    (MAP), or expected a posteriori (EAP). Content balancing, item exposure
    control, and shadow testing are configurable through constraint
    functions. The implemented methods follow Cheng (2009)
    <doi:10.1007/s11336-009-9123-2> and de la Torre (2011)
    <doi:10.1007/s11336-011-9207-7>. Designed for real-time, item-by-item
    adaptive applications.