diagnose.ppmlasso: Create diagnostic plots for a fitted point process model.

In ppmlasso: Point Process Models with LASSO-Type Penalties

Create diagnostic plots for a fitted point process model.

Description

This function is analogous to the diagnose.ppm function of the spatstat package.

Usage

## S3 method for class 'ppmlasso'
diagnose(object, ...)

Arguments

object	A fitted regularisation path of point process models. The diagnostic plots will be created for the model that optimises the given criterion.
...	Other arguments for producing diagnostic plots, as given by the diagnose.ppm function of the spatstat package.

Details

See the help file for diagnose.ppm in the spatstat package for further details of diagnostic plots.

Author(s)

Ian W. Renner

References

Baddeley, A.J. & Turner, R. (2005). Spatstat: an R package for analyzing spatial point patterns. Journal of Statistical Software 12, 1-42.

See Also

envelope.ppmlasso, for other goodness-of-fit functions inherited from spatstat.

Examples

data(BlueMountains)
sub.env = BlueMountains$env[BlueMountains$env$Y > 6270 & BlueMountains$env$X > 300,]
sub.euc = BlueMountains$eucalypt[BlueMountains$eucalypt$Y > 6270 & BlueMountains$eucalypt$X > 300,]
ppm.form = ~poly(FC, TMP_MIN, TMP_MAX, RAIN_ANN, degree = 2) + poly(D_MAIN_RDS, D_URBAN, degree = 2)
ppm.fit  = ppmlasso(ppm.form, sp.xy = sub.euc, env.grid = sub.env, sp.scale = 1, n.fits = 20,
writefile = FALSE)
diagnose(ppm.fit, which = "smooth", type = "Pearson")

ppmlasso documentation built on Dec. 1, 2022, 5:09 p.m.