muEst: muEst function

In bentaylor1/lgcp: Log-Gaussian Cox Process

Description

Computes a non-parametric estimate of mu(t). For the purposes of performing prediction, the alternatives are: (1) use a parameteric model as in Diggle P, Rowlingson B, Su T (2005), or (2) a constantInTime model.

Usage

muEst(xyt, ...)

Arguments

xyt	an stppp object
...	additional arguments to be passed to lowess

Value

object of class temporalAtRisk giving the smoothed mut using the lowess function

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

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

See Also

temporalAtRisk, constantInTime, ginhomAverage, KinhomAverage, spatialparsEst, thetaEst, lambdaEst

bentaylor1/lgcp documentation built on May 12, 2019, 2:09 p.m.