plot.locppm {spatstat.local}

Plot a Locally Fitted Poisson or Gibbs Model

Description

Plot an object of class "locppm" representing a locally-fitted Poisson or Gibbs point process model.

Usage

## S3 method for class 'locppm'
plot(x, ..., what = "cg", which = NULL)

## S3 method for class 'locppm'
contour(x, ..., what = "cg", which = NULL)

Arguments

x

A locally-fitted Poisson or Gibbs point process model (object of class "locppm").

...

Arguments passed to plot.ssf to control the plot.

what

What quantity to display. A character string. The default is to display the fitted coefficient vectors.

which

Which component(s) of the vector-valued quantity to display. An index or index vector.

Details

These are methods for the generic commands plot and contour, for the class "locppm".

The argument what specifies what quantity will be displayed:

"cg"	Fitted coefficients of local model
"vg"	Local variance matrix for Gibbs model
"vh"	Local variance matrix for homogeneous model
"tg"	t-statistics based on "coefs" and "vg"

Typically these quantities are vector-valued (matrices are converted to vectors). The argument which, if present, specifies which elements of the vector are displayed. It may be any kind of index for a numeric vector.

The plotting is performed by plot.ssf.

Value

NULL.

Author(s)

Adrian Baddeley [e-mail].

References

Baddeley, A. (2017) Local composite likelihood for spatial point patterns. Spatial Statistics 22, 261–295. DOI: 10.1016/j.spasta.2017.03.001

Baddeley, A., Rubak, E. and Turner, R. (2015) Spatial Point Patterns: Methodology and Applications with R. Chapman and Hall/CRC Press.

See Also

locppm, methods.locppm, plot, plot.default

Examples

   fit <- locppm(swedishpines, ~1, sigma=9, nd=20,
             vcalc="hessian", locations="coarse")
   plot(fit)  
   plot(fit, what="Vg")