Changes in version 0.1.4                        

  - Added preflight data-quality checks to the generic analysis
    template, including response-family validation, non-finite-value
    detection, constant predictor detection, and summaries of missing
    and unique values.
  - Added an optional predictor-correlation screen to the template.
    Because the current candidate set fits one environmental predictor
    per model, the screen reports potentially redundant ecological
    hypotheses without applying VIF or removing variables automatically.
  - Added exports for the data-quality summary, predictor correlations,
    and the complete preflight-check object.
  - Added an automated test ensuring that the installed generic template
    exists, is non-empty, and can be parsed by R.
  - Restored automatic export of a multi-page DHARMa_diagnostics.pdf,
    with the residual panels and a formal-test summary for every
    selected response model.

                 Changes in version 0.1.3 (2026-09-30)                  

  - Published on CRAN on 30 September 2026.

  - Assigned the permanent CRAN DOI 10.32614/CRAN.package.ecoGLMM.

  - Standardized the complete real-data workflow and documentation in
    English.

  - Added complete author metadata and ORCID identifiers for André
    Felipe Carneiro dos Santos, Bruna Martins Bezerra, and Bárbara Lins
    Caldas de Moraes.

  - Restored MuMIn::r.squaredGLMM() as the primary R-squared method to
    match the original dissertation pipeline.

  - Added parallel Nakagawa R-squared results from
    performance::r2_nakagawa() in explicitly labelled columns.

                        Changes in version 0.1.2                        

  - Corrected likelihood-ratio-test degrees of freedom to report the
    difference in model parameters rather than the total parameter
    count.
  - Removed unused colour and fill labels from additive effect plots.

                        Changes in version 0.1.1                        

  - Corrected the Authors@R role field in DESCRIPTION.

                        Changes in version 0.1.0                        

  - Initial research release.
  - Fits additive and predictor-by-period GLMM candidate sets.
  - Supports beta, Gamma, Gaussian, Poisson, and negative-binomial
    families.
  - Calculates AICc, Akaike weights, evidence ratios, and
    competitive-model flags.
  - Compares nested additive and interaction models with
    likelihood-ratio tests.
  - Extracts coefficients, Wald confidence intervals, and Nakagawa
    R-squared.
  - Runs DHARMa uniformity, dispersion, and outlier diagnostics.
  - Produces marginal-effect, model-selection, and coefficient figures.
  - Exports analysis tables and figures.