NEWS

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enmpa 0.1.9 (2024-12-20)

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• New Functions:

  • Added three new functions: resp2var(), jackknife(), and plot_jk().
    • resp2var(): Transforms species probability data into a two-dimensional environmental space for visualization.
    • jackknife(): Evaluates the influence of each variable on the overall model using four distinct metrics: ROC-AUC, TSS, AICc, and Deviance. This function facilitates jackknife resampling to assess variable importance.
    • plot_jk(): A function to plot the results of the jackknife resampling.

• Bug Fixes:

  • Fixed a bug in calibration_glm() related to runtime calculation errors.

enmpa 0.1.8 (2024-06-19)

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• New Classes:

  • Added two new classes: enmpa_calibration and enmpa_fitted_models.
    • These classes help manage the list outputs from the functions calibration_glm and fit_selected.
    • Each class has two associated methods: summary() and print(), which provide summaries and print representations of the objects, respectively.

• Updates to predict_glm:

  • Added a new flag extrapolation_type to indicate the type of extrapolation:
    • "E": Free extrapolation
    • "NE": No extrapolation
    • "EC": Extrapolation with clamping
  • The flag var_to_clamp was replaced by restricted_vars.
  • The flag clamping was removed.

• Updates to model_validation:

  • Now includes 'residual deviance' as a validation metric.

enmpa 0.1.5 (2023-12-01)

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• Initial CRAN submission.