The Squealer: Sensification of model exploration and model misfit

Andrew Gelman; Andrew H. Jaffe; Eliot Carlson; Philip Greengard

The Squealer: Sensification of model exploration and model misfit

Data Analysis, Statistics and Probability 2026-06-29 v1 Cosmology and Nongalactic Astrophysics Methodology

Authors: Andrew Gelman , Andrew H. Jaffe , Eliot Carlson , Philip Greengard

Abstract

We introduce a method for visual and auditory feedback when exploring the fit of a model to data. Starting with a best-fit curve fit to data, the user can drag the curve to a new position and the computer will emit a squeal, becoming louder and more unpleasant as the discrepancy between curve and data increases. We demonstrate with four examples: a two-parameter curve fit to golf putting data, a four-parameter curve fit to dilution assays, a fit to cosmological data sensitive to the parameters of the Big Bang model, and a nonparametric Gaussian process fit to temperature readings.

Keywords

model fitting visual feedback auditory feedback sensory substitution interactive exploration Gaussian process

Cite

@article{arxiv.2606.29842,
  title  = {The Squealer: Sensification of model exploration and model misfit},
  author = {Andrew Gelman and Andrew H. Jaffe and Eliot Carlson and Philip Greengard},
  journal= {arXiv preprint arXiv:2606.29842},
  year   = {2026}
}

Comments

18 pages, 11 figures. Submitted to the Journal of Computational and Graphical Statistics