Changes in version 0.1.0 (2026-11-07)                  

First release.

Fitting

  - nutrigon_fit() fits a quadratic response surface and locates the
    nutritional optimum with a hybrid estimator: the closed-form
    stationary point when it is admissible (inside the design hull,
    correct curvature sign), otherwise a constrained Monte Carlo search
    summarised by the point with the highest (or lowest) fitted value.
    model_type selects ordinary least squares ("lm"), a generalized
    linear model with any family including quasi-families ("glm";
    optimum located on the link scale), or a linear mixed-effects model
    ("lmer"; population-level optimum; requires lme4 and lmerTest).
  - nutrigon_coefs(), nutrigon_elongation(), nutrigon_snr() and
    nutrigon_curvature() return the fitted quadratic coefficients, the
    curvature elongation ratio, the signal-to-noise ratio, and local
    Gaussian/mean curvature with a surface-area ratio.

Inference

  - nutrigon_compare() estimates the angular separation between two
    optima with a percentile bootstrap interval that refits both
    surfaces in every replicate. Resampling is by case (default) or
    stratified within design points, paired or unpaired. Returns the
    locations of the optima, each surface's angular support, the
    bootstrap distribution and the Monte Carlo fallback rate.
  - nutrigon_matrix() builds the N x N angular trade-off matrix with
    joint bootstrap uncertainty (the same replicate of each surface is
    used in every pair) and the bootstrap stability of a hierarchical
    clustering.
  - nutrigon_equivalence() tests whether two optima are aligned within a
    pre-specified angle.

Coverage check

  - nutrigon_build_grid() simulates a validation grid, either on the
    user's own design and at the signal-to-noise ratio of the fitted
    surfaces (recommended) or on a generic rail design.
  - nutrigon_check() estimates the coverage expected for one result from
    the nearest grid configurations, with a Wilson interval, excluding
    near-zero angles and warning when the grid comes from a different
    design.

Plotting helpers

  - nutrigon_grid(), nutrigon_hull() and nutrigon_region_polygon()
    prepare fitted surfaces for ggplot2.

Data

  - lee_drosophila, zanco_survival, zanco_wingsize,
    zanco_tradeoff_matrix and nutrigon_validation_grid.