bc.ppm: Bias Correction for Fitted Model

In spatstat.model: Parametric Statistical Modelling and Inference for the 'spatstat' Family

Bias Correction for Fitted Model

Description

Applies a first-order bias correction to a fitted model.

Usage

  bc(fit, ...)

  ## S3 method for class 'ppm'
bc(fit, ..., nfine = 256)

Arguments

fit	A fitted point process model (object of class "ppm") or a model of some other class.
...	Additional arguments are currently ignored.
nfine	Grid dimensions for fine grid of locations. An integer, or a pair of integers. See Details.

Details

This command applies the first order Newton-Raphson bias correction method of Baddeley and Turner (2014, sec 4.2) to a fitted model. The function bc is generic, with a method for fitted point process models of class "ppm".

A fine grid of locations, of dimensions nfine * nfine or nfine[2] * nfine[1], is created over the original window of the data, and the intensity or conditional intensity of the fitted model is calculated on this grid. The result is used to update the fitted model parameters once by a Newton-Raphson update.

This is only useful if the quadrature points used to fit the original model fit are coarser than the grid of points specified by nfine.

Value

A numeric vector, of the same length as coef(fit), giving updated values for the fitted model coefficients.

Author(s)

\adrian

and \rolf.

References

Baddeley, A. and Turner, R. (2014) Bias correction for parameter estimates of spatial point process models. Journal of Statistical Computation and Simulation 84, 1621–1643. DOI: 10.1080/00949655.2012.755976

See Also

rex

Examples

  fit <- ppm(cells ~ x, Strauss(0.07))
  coef(fit)
  if(!interactive()) {
    bc(fit, nfine=64)
  } else {
    bc(fit)
  }

spatstat.model documentation built on Sept. 30, 2024, 9:26 a.m.