A function to compute the conditional type-probabilities
from a multivariate LGCP. See the vignette "Bayesian_lgcp"
for a full explanation of this.
Usage
condProbs(obj)
Arguments
obj
an lgcpPredictMultitypeSpatialPlusParameters
object
Value
an lgcpgrid object containing the consitional
type-probabilities for each type
Details
We suppose there are K point types of interest. The model
for point-type k is as follows:
X_k(s) ~
Poisson[R_k(s)]
R_k(s) = C_A lambda_k(s)
exp[Z_k(s)beta_k+Y_k(s)]
Here X_k(s) is the number of events of type k in the
computational grid cell containing the point s, R_k(s) is
the Poisson rate, C_A is the cell area, lambda_k(s) is a
known offset, Z_k(s) is a vector of measured covariates and
Y_i(s) where i = 1,...,K+1 are latent Gaussian processes on
the computational grid. The other parameters in the model
are beta_k , the covariate effects for the kth type; and
eta_i = [log(sigma_i),log(phi_i)], the parameters of the
process Y_i for i = 1,...,K+1 on an appropriately
transformed (again, in this case log) scale.
The term 'conditional probability of type k' means the
probability that at a particular location there will be an
event of type k, which denoted p_k.