SQUIRE: Statistical Quality-Assured Integrated Response Estimation
Provides systematic geometry-adaptive parameter optimization with
statistical validation for experimental biological data. Combines ANOVA-based
validation with systematic constraint configuration testing (log-scale,
positive domain, Euclidean) through T,P,E testing. Only proceeds with
parameter optimization when statistically significant biological effects
are detected, preventing over-fitting to noise. Uses 'GALAHAD' trust region methods with constraint projection from Conn et al. (2000)
<doi:10.1137/S1052623497325107>, ANOVA-based validation following Fisher
(1925) <doi:10.1007/978-1-4612-4380-9_6>, and effect size calculations
per Cohen (1988, ISBN:0805802835). Designed for structured experimental
data including kinetic curves, dose-response studies, and treatment
comparisons where appropriate parameter constraints and statistical
justification are important for meaningful biological interpretation.
Developed at the Minnesota Center for Prion Research and Outreach at
the University of Minnesota.
Documentation:
Downloads:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=SQUIRE
to link to this page.
[aut, cre]