exceedProbs

vector of threshold levels for the indicator function

threshold

default 'upper' giving exceedance probabilities, alternative is 'lower', which gives 'subordinate probabilities'

direction

This function can be called using <code>MonteCarloAverage</code> (see <code>fun3</code> the examples in the help file for
<a rd-options="" href="/link/MonteCarloAverage?package=lgcp&version=1.8" data-mini-rdoc="lgcp::MonteCarloAverage">MonteCarloAverage</a>). It computes exceedance probabilities,
$$P[\exp(Y_{t_1:t_2})&gt;k],$$
that is the probability that the relative reisk exceeds threshold $k$. Note that it is possible
to pass vectors of tresholds to the function, and the exceedance probabilities will be computed for each
of these.

Spatial and spatio-temporal modelling of point patterns using the
log-Gaussian Cox process. Bayesian inference for spatial, spatiotemporal,
multivariate and aggregated point processes using Markov chain Monte Carlo. See Benjamin M. Taylor, Tilman M. Davies, Barry S. Rowlingson, Peter J. Diggle (2015) <doi:10.18637/jss.v063.i07>.

Benjamin Taylor

lgcp

Log-Gaussian Cox Process

exceedProbs function

This function can be called using <code>MonteCarloAverage</code> (see <code>fun3</code> the examples in the help file for
<a rd-options='' href='MonteCarloAverage'>MonteCarloAverage</a>). It computes exceedance probabilities,
$$P[\exp(Y_{t_1:t_2})&gt;k],$$
that is the probability that the relative reisk exceeds threshold $k$. Note that it is possible
to pass vectors of tresholds to the function, and the exceedance probabilities will be computed for each
of these.

exceedProbs: exceedProbs function

Description

Usage

Arguments

Value

See Also