ginhomAverage {lgcp} | R Documentation |
ginhomAverage function
Description
A function to estimate the inhomogeneous pair correlation function for a spatiotemporal point process. See equation (8) of Diggle P, Rowlingson B, Su T (2005).
Usage
ginhomAverage(
xyt,
spatial.intensity,
temporal.intensity,
time.window = xyt$tlim,
rvals = NULL,
correction = "iso",
suppresswarnings = FALSE,
...
)
Arguments
xyt |
an object of class stppp |
spatial.intensity |
A spatialAtRisk object |
temporal.intensity |
A temporalAtRisk object |
time.window |
time interval contained in the interval xyt$tlim over which to compute average. Useful if there is a lot of data over a lot of time points. |
rvals |
Vector of values for the argument r at which g(r) should be evaluated (see ?pcfinhom). There is a sensible default. |
correction |
choice of edge correction to use, see ?pcfinhom, default is Ripley isotropic correction |
suppresswarnings |
Whether or not to suppress warnings generated by pcfinhom |
... |
other parameters to be passed to pcfinhom, see ?pcfinhom |
Value
time average of inhomogenous pcf, equation (13) of Brix and Diggle 2001.
References
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/
Baddeley AJ, Moller J, Waagepetersen R (2000). Non-and semi-parametric estimation of interaction in inhomogeneous point patterns. Statistica Neerlandica, 54, 329-350.
Brix A, Diggle PJ (2001). Spatiotemporal Prediction for log-Gaussian Cox processes. Journal of the Royal Statistical Society, Series B, 63(4), 823-841.
Diggle P, Rowlingson B, Su T (2005). Point Process Methodology for On-line Spatio-temporal Disease Surveillance. Environmetrics, 16(5), 423-434.
See Also
KinhomAverage, spatialparsEst, thetaEst, lambdaEst, muEst