spatialparsEst {lgcp}R Documentation

spatialparsEst function

Description

Having estimated either the pair correlation or K functions using respectively ginhomAverage or KinhomAverage, the spatial parameters sigma and phi can be estimated. This function provides a visual tool for this estimation procedure.

Usage

spatialparsEst(
  gk,
  sigma.range,
  phi.range,
  spatial.covmodel,
  covpars = c(),
  guess = FALSE
)

Arguments

gk

an R object; output from the function KinhomAverage or ginhomAverage

sigma.range

range of sigma values to consider

phi.range

range of phi values to consider

spatial.covmodel

correlation type see ?CovarianceFct

covpars

vector of additional parameters for certain classes of covariance function (eg Matern), these must be supplied in the order given in ?CovarianceFct

guess

logical. Perform an initial guess at paramters? Alternative (the default) sets initial values in the middle of sigma.range and phi.range. NOTE: automatic parameter estimation can be can be unreliable.

Details

To get a good choice of parameters, it is likely that the routine will have to be called several times in order to refine the choice of sigma.range and phi.range.

Value

rpanel function to help choose sigma nad phi by eye

References

  1. Benjamin M. Taylor, Tilman M. Davies, Barry S. Rowlingson, Peter J. Diggle (2013). Journal of Statistical Software, 52(4), 1-40. URL http://www.jstatsoft.org/v52/i04/

  2. Baddeley AJ, Moller J, Waagepetersen R (2000). Non-and semi-parametric estimation of interaction in inhomogeneous point patterns. Statistica Neerlandica, 54, 329-350.

  3. Brix A, Diggle PJ (2001). Spatiotemporal Prediction for log-Gaussian Cox processes. Journal of the Royal Statistical Society, Series B, 63(4), 823-841.

  4. Diggle P, Rowlingson B, Su T (2005). Point Process Methodology for On-line Spatio-temporal Disease Surveillance. Environmetrics, 16(5), 423-434.

See Also

ginhomAverage, KinhomAverage, thetaEst, lambdaEst, muEst


[Package lgcp version 2.0 Index]