SQUIRE: Statistical Quality-Assured Integrated Response Estimation

Author: Richard A. Feiss
Version: 1.0.1
License: MIT
Institution: Minnesota Center for Prion Research and Outreach (MNPRO), University of Minnesota
GitHub: https://github.com/RFeissIV

Overview

SQUIRE (Statistical Quality-Assured Integrated Response Estimation) provides a structured workflow for biological parameter estimation that combines statistical validation with systematic testing of constraint configurations to improve optimization reliability.

SQUIRE addresses common challenges in biological parameter estimation by organizing existing statistical and optimization methods into a coherent workflow. The package combines:

1. Statistical validation - ANOVA-based testing ensures optimization is only performed on data with significant treatment effects
2. Systematic constraint configuration testing - Evaluates combinations of T (log-scale), P (positive orthant), and E (Euclidean) parameter constraints
3. Geometry-aware optimization - Applies selected constraints during parameter estimation using GALAHAD
4. Validation-gated workflow - Prevents optimization on statistically insignificant data

SQUIRE integrates with the GALAHAD optimization package for geometry-adaptive trust-region methods.

Key Features