lgcpForecast: lgcpForecast function

In bentaylor1/lgcp: Log-Gaussian Cox Process

Description

Function to produce forecasts for the mean field Y at times beyond the last time point in the analysis (given by the argument T in the function lgcpPredict).

Usage

lgcpForecast(lg, ptimes, spatial.intensity, temporal.intensity,
  inclusion = "touching")

Arguments

lg	an object of class lgcpPredict
ptimes	vector of time points for prediction. Must start strictly after last inferred time point.
spatial.intensity	the fixed spatial component: an object of that can be coerced to one of class spatialAtRisk
temporal.intensity	the fixed temporal component: either a numeric vector, or a function that can be coerced into an object of class temporalAtRisk
inclusion	criterion for cells being included into observation window. Either 'touching' or 'centroid'. The former includes all cells that touch the observation window, the latter includes all cells whose centroids are inside the observation window.

Value

forcasted relative risk, Poisson intensities and Y values over grid, together with approximate variance.

References

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

See Also

lgcpPredict

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