dsm (version 2.3.3)

vis_concurvity: Visualise concurvity between terms in a GAM

Description

Plot measures of how much one term in the model could be explained by another. When values are high, one should consider re-running variable selection with one of the offending variables removed to check for stability in term selection.

Usage

vis_concurvity(model, type = "estimate")

Arguments

model

fitted model

type

concurvity measure to plot, see concurvity

Author

David L Miller

Details

These methods are considered somewhat experimental at this time. Consult concurvity for more information on how concurvity measures are calculated.

Examples

if (FALSE) {
library(Distance)
library(dsm)

# load the Gulf of Mexico dolphin data (see ?mexdolphins)
data(mexdolphins)

# fit a detection function and look at the summary
hr.model <- ds(distdata, truncation=6000,
               key = "hr", adjustment = NULL)

# fit a simple smooth of x and y to counts
mod1 <- dsm(count~s(x,y)+s(depth), hr.model, segdata, obsdata)

# visualise concurvity using the "estimate" metric
vis_concurvity(mod1)
}