---
title: "Ecosystem update — September 2026"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{Ecosystem update — September 2026}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

## eyeprocess 0.11.1 published on CRAN

`eyeprocess` **0.11.1** was published on CRAN on **28 September 2026**.
The canonical package page is <https://CRAN.R-project.org/package=eyeprocess>
and the package DOI is <https://doi.org/10.32614/CRAN.package.eyeprocess>.

The release channels are intentionally distinct: CRAN currently provides
0.11.1, GitHub provides the newer stable `v0.12.0` release, and `master`
continues as the 0.12.0.9000 development line. Analyses should report the
version actually installed rather than treating these channels as equivalent.

## Related downstream modelling addition

The related Python package **gpbiometricspy** now includes a fully exact-main-certified crossed participant–item Gaussian hierarchical location–scale model with **one location random slope for each crossed factor**.

This does not modify `eyeprocess`, its vendor-neutral measurement workflows, psychometric/process-analysis surface, or release record. The new gpbiometricspy method is a downstream modelling option for appropriately designed continuous repeated outcomes after acquisition, timing, validity, preprocessing, and construct-evidence questions have been handled explicitly.

Certified gpbiometricspy PR #129 is pinned to merge SHA `d078e0366ace49c3ebeb2f6800bad6394d70631e`: 14/14 exact-main push workflow families, 12/12 OS/Python matrix lanes, 782/782 tests, 14,015/14,015 statements, and 6,757/6,776 raw branches (99.7196%). The frozen `gpbiometrics 2.0.0` R-parity surface remains 406/406 and is unchanged.

- [Crossed participant–item random-slope guide](https://stefanosbalaskas.github.io/gpbiometricspy/methods/crossed-random-slopes-location-scale/)
- [gpbiometricspy PR #129](https://github.com/stefanosbalaskas/gpbiometricspy/pull/129)

The scientific boundary remains important: crossed random slopes estimate conditional-association heterogeneity; they do not establish measurement validity, causal effects, participant traits, stimulus quality, or latent psychological states.