All functions

devianceResids()

Calculate binary outcome deviance residuals using probability predictions

Features

Landscape and host feature (variable) data

filterRareCommon()

Filter rare response variables from the data

gfData

Regression data from Fitzpatrick et al 2014

mrFlashlight()

mrFlashlight: Wrapper to run mutlti-response model agnostic interpretable machine learning analyses.

mrIMLperformance()

Wrapper to calculate performance metrics (Mathews correlation coefficent, sensitivity and specificity) for each model for each response variable.

mrIMLpredicts()

Wrapper to generate multi-response predictive models.

mrInteractions()

Wrapper to calculate and plot summed interactions of features across response variables. Bases on Greenwell et al 2018

mrPlot_interactions()

Plots global interactions as well as individual repsonse interaction importance.

mrProfileplot()

mrProfileplot: Wrapper to plot mutlti-response model agnostic profile plots (partial dependences and accumulated local effects).

mrVip()

Wrapper to estimate model-agnostic variable importance for multi-response models.

plot_vi()

Plots global importance (i.e. cumulative importance of all features for all response variables) and individual response importance.

readSnpsPed()

Conversion to single column per locus from plink file via LEA functionality

resist_components()

Calculates resistance components from a list of pairwise resistance surfaces.

Responsedata

Viral single nucleuotide polymorphism (SNP) data.

vintTidy()

vintTidy: Interaction effects for tidymodel objects

mrBenchmark()

Compare and benchmark disease outbreak risk among and within groups

mrLocalExplainer()

Run local explanation methods for individual data points

plot_vi_biosecurity()

Plots global importance (i.e. cumulative importance of all features for all response variables) and individual response importance.