mcmc_stpp_nonunif {stpphawkes} | R Documentation |
This function computes the posterior of a spatio-temporal exponential decay Hawkes model using Metropolis-with-in-Gibbs sampling.
mcmc_stpp_nonunif(
data,
poly,
t_max = max(data$t),
t_mis = NULL,
param_init = NULL,
mcmc_param = NULL,
branching = TRUE,
print = TRUE,
sp_clip = TRUE
)
data |
- A DataFrame containing |
poly |
- matrix defining polygon ( |
t_max |
- maximum time value (default = max(times)) |
t_mis |
- vector of two elements describing missing time range (default = NULL) |
param_init |
- list of parameters of initial guess (default = NULL, will start with MLE) |
mcmc_param |
- list of mcmc parameters |
branching |
- using branching structure in estimation (default = TRUE) |
print |
- print progress (default = TRUE) |
sp_clip |
- when simulating missing data spatial points, clip spatial region back to observed region (default = TRUE) |
The default is to estimate the branching structure.
The model will also account to missing data if t_mis
is provided.
A DataFrame containing the mcmc samples