spatstat.local (version 5.1-0)

predict.loccit: 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 loccit
predict(object, ...)
  # S3 method for loccit
fitted(object, ..., new.coef=NULL)

Value

An object of class "ssf" as described in ssf.

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.

Author

Adrian Baddeley .

Details

The fitted intensity is computed.

References

Baddeley, A. (2017) Local composite likelihood

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)