# enmpa 0.1.9
- 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
- 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