View source: R/parameterEstimation.R
ginhomAverage | R Documentation |
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).
ginhomAverage(
xyt,
spatial.intensity,
temporal.intensity,
time.window = xyt$tlim,
rvals = NULL,
correction = "iso",
suppresswarnings = FALSE,
...
)
xyt |
an object of class stppp |
spatial.intensity |
A spatialAtRisk object |
temporal.intensity |
A temporalAtRisk object |
time.window |
time interval contained in the interval xyt$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 |
time average of inhomogenous pcf, equation (13) of Brix and Diggle 2001.
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.
KinhomAverage, spatialparsEst, thetaEst, lambdaEst, muEst
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