Software
Code you can run
Packages, teaching tools, and the code behind the papers. Everything here is public on GitHub.
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anytimeCAT
In development — v0.1 planned October 2026R package: anytime-valid confidence sequences for the latent ability in computerized adaptive testing (2PL), a fixed-sample Wald baseline, a censored MLE, and a CAT simulator with sequence-based stopping. Repository opens with v0.1.
Paper: Yang (2026), Precision and Robustness in Adaptive Testing (dissertation)
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Interactive teaching tool for the Central Limit Theorem: choose a population, draw samples, and watch the sampling distribution form. Live at hardy1yang.github.io/clt-interactive-course.
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R code that reproduces the simulations and figures of the generalized Robbins–Monro paper.
Paper: Journal of Mathematical Psychology, 2024 — doi:10.1016/j.jmp.2024.102855
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Random forest aggregation with the General Condorcet Model for imbalanced classification; full experimental pipeline over 17 benchmark datasets.
Paper: Yang, Ho, & Hsu, Journal of Classification (minor revision)
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Specification-driven template for turning course notes into slides, worksheets, quizzes, interactive pages, and a course-specific AI teaching assistant; used in the Taiwan Economic Association workshops.