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
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/
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.