SDALGCPexceedance

an object of class "Pred.SDALGCP" obtained as result of a call to <code><a rd-options="" href="/link/SDALGCPPred?package=SDALGCP&version=0.4.0" data-mini-rdoc="SDALGCP::SDALGCPPred">SDALGCPPred</a></code>.

either a vector of numbers or a vector of single value.

thresholds

logical; TRUE for spatially continuous relative risk and FALSE for region specific relative risk. default is TRUE

continuous

Computes the exceedance probability for a given threshold of the spatially continuous relative risk or the region specific relative risk from the object of class "Pred.SDALGCP".

internal

Provides a computationally efficient discrete approximation to log-Gaussian Cox process model for spatially aggregated disease count data. It uses Monte Carlo Maximum Likelihood for model parameter estimation as proposed by Christensen (2004) <doi: 10.1198/106186004X2525> and delivers prediction of spatially discrete and continuous relative risk. It performs inference for static spatial and spatio-temporal dataset. The details of the methods are provided in Johnson et al (2019) <doi:10.1002/sim.8339>.

Olatunji Johnson

SDALGCP

Spatially Discrete Approximation to Log-Gaussian Cox Processes
for Aggregated Disease Count Data

Emanuele Giorgi

Peter Diggle

SDALGCPexceedance function

an object of class "Pred.SDALGCP" obtained as result of a call to <code><a rd-options='' href='SDALGCPPred'>SDALGCPPred</a></code>.

SDALGCPexceedance: Exceedance probability of the relative risk

Description

Usage

Arguments

Value