Nonlinear Search
Model-family comparison covers kernel smoothing, polynomial regression, sinusoidal regression, and Fourier-series regression with explicit complexity tuning.
Methods Evidence
Public-safe evidence documenting statistical methods that I apply in analysis work: nonlinear model search, Fourier regression, interpretable GLMs, validation, calibration, and threshold analysis. The artifacts are derived from graduate statistics coursework.
Statistics Evidence
The repo turns private coursework artifacts into public-safe, runnable methods evidence with clean titles, sanitized data, generated figures, model-comparison tables, and skill summaries.
Methods
Model-family comparison covers kernel smoothing, polynomial regression, sinusoidal regression, and Fourier-series regression with explicit complexity tuning.
The nonlinear project separates high in-sample fit from plausible behavior beyond the observed range and reports residual diagnostics for the selected model.
The clinical project compares staged logistic models with repeated stratified cross-validation and selects the primary model by probability-scale log loss.
The risk model includes calibration tables and threshold metrics, including sensitivity, specificity, PPV, and NPV at candidate review cutoffs.
Inspect In Source Repo
The repo uses a `make all` pipeline to regenerate public data where appropriate, run analyses, build figures and report summaries, and validate the public boundary.
Safety Boundary
The project publishes public-safe analysis code, sanitized data, generated figures, and method summaries. It does not publish private course prompts, syllabi, lecture material, source documents, or direct clinical record identifiers.