Not always is there enough data or sufficient information to robustly infer the suitable habitat or niche of a species. As many SDM algorithms are essentially regression models, similar assumptions about model convergence, homogeneity of residuals and inferrence usually apply (although often ignored). This function simply checks the respective input object for common issues or mistakes.
Usage
check(obj, stoponwarning = FALSE)
# S4 method for class 'ANY'
check(obj, stoponwarning = FALSE)
Arguments
- obj
A
BiodiversityDistribution
,DistributionModel
orBiodiversityScenario
object.- stoponwarning
logical
Should check return a stop if warning is raised? (Default:FALSE
).
Details
Different checks are implemented depending on the supplied object
Checks if there are less than 200 observations
TODO: Add rm_insufficient_covs link
Check model convergence
Check if model is found
Check if coefficients exist
Check if there are unusal outliers in prediction (using 10median absolute deviation)
Check if threshold is larger than layer