predict.loccit {spatstat.local}

Prediction for Locally-Fitted Cox or Cluster Model

Description

Computes the fitted intensity of a locally-fitted Cox process or cluster process model.

Usage

  ## S3 method for class 'loccit'
predict(object, ...)

  ## S3 method for class 'loccit'
fitted(object, ..., new.coef=NULL)

Arguments

object

Locally fitted point process model (object of class "loccit" fitted by loccit).

...

Arguments passed to predict.locppm.

new.coef

New values for the fitted coefficients. A matrix in which each row gives the fitted coefficients at one of the quadrature points of the model.

Details

The fitted intensity is computed.

Value

An object of class "ssf" as described in 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

loccit, predict.locppm.

Examples

  X <- redwood[owin(c(0,1), c(-1,-1/2))]
  fit <- loccit(X, ~1, "Thomas", nd=5, control=list(maxit=20))
  lam <- predict(fit)