ttestmap {spatstat.local}

Test of Effect in Locally Fitted Point Process Model

Description

Perform a local t-test for the presence of a covariate effect in a locally fitted Poisson or Gibbs point process model.

Usage

ttestmap(object, term, ...,
         method = c("exact", "hessian", "taylor"),
         grid = FALSE, 
         ngrid = NULL, grideps = NULL,
         verbose = TRUE)

Arguments

object

Locally fitted Poisson or Gibbs point process model (object of class "locppm").

term

Term to be dropped from the model. A character string matching a term in the model formula

...

Ignored.

method

Choice of method to be used to evaluate the t statistic. See Details.

grid

Logical. If FALSE, compute the test statistic at all quadrature points of the model. If TRUE, compute at a coarse grid of locations.

ngrid

Number of grid points (in each axis direction) for the coarse grid. Incompatible with grideps.

grideps

Spacing (horizontal and vertical) between grid points for the coarse grid. Incompatible with ngrid.

verbose

Logical value indicating whether to print progress reports.

Details

The argument object should be a locally-fitted Poisson or Gibbs point process model (object of class "locppm" created by locppm).

This function computes the local t test statistic for the test that a particular covariate effect in the model is zero. This is described in Baddeley (2016, sections 3 and 5).

Value

Object of class "ssf".

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

Examples

 fit <- with(copper,
        locppm(Points, ~D, covariates=list(D=distfun(Lines)), nd=c(7,15)))
 plot(ttestmap(fit, "D"))