Model Evaluation and Analysis
Apply threshold(s) to model predictions
Arrange plots
Area Under the Curve
Boyce Index
Label predictions according to their confusion matrix category
Confusion matrix
Explained deviance
Measures of model prediction error.
Evaluate a model based on the elements of a confusion matrix.
Evenness in a binary vector.
Get bins of continuous values.
Get model equation
Prediction threshold for a given criterion
Hosmer-Lemeshow goodness of fit
Munch inputs into 'obs' and 'pred' vectors
Log-likelihood
Lollipop chart
Multivariate Environmental Similarity Surfaces based on a data frame
Miller's calibration satistics for logistic regression models
Extract observed and predicted, or predictor, values from a model obje...
Model Evaluation and Analysis
Methods implemented in modEvA functions
Multiple model evaluation
Overlap Analysis
Optimize the classification threshold for a pair of related model eval...
Optimize threshold for model evaluation.
Plot model coefficients with confidence intervals
Plot a generalized linear model
Plot the density of predicted or predictor values for presences and ab...
Plot predicted values for presences and absences, optionally classifie...
Prevalence
Pseudo-R-squared measures for binary-response models
Observed and predicted values from presence points and a raster map.
Reclassify continuous values based on quantiles
Shrink or stretch a vector to make it range between 0 and 1
Root mean square error
R-squared measures for GLMs
Similarity measures
Standardize to 0-1 (or vice-versa)
Threshold-based measures of model evaluation
Variable importance.
Variation partitioning
Analyses species distribution models and evaluates their performance. It includes functions for variation partitioning, extracting variable importance, computing several metrics of model discrimination and calibration performance, optimizing prediction thresholds based on a number of criteria, performing multivariate environmental similarity surface (MESS) analysis, and displaying various analytical plots. Initially described in Barbosa et al. (2013) <doi:10.1111/ddi.12100>.