Summary of model fitting functions offered listing the key arguments for each.
Function
Key arguments
fit_hawkes()
times - a vector of numeric occurrence times.
parameters - a vector of named starting values for \(\mu\) (mu), \(\alpha\) (alpha), and \(\beta\) (beta).
marks - optional, a vector of marks (\(m(t)\)).
fit_mhawkes()
times - a vector of numeric occurrence times.
stream - character vector specifying the stream ID of each observation in times.
parameters - a vector of named starting values for \(\mu\) (mu), \(\alpha\) (alpha), and \(\beta\) (beta).
fit_hawkes_cbf()
As fit_hawkes() plus
background - some assumed time dependent background function \(\mu(t)\).
background_integral - the integral of background.
background_parameters - parameter starting values for \(\mu(t)\).
( \(^*\)Note, \(\texttt{mu}\) in parameters will be ignored)
fit_lgcp()
locs - a named data frame of event locations, x, y, and t (optional).
sf - a polygon of the spatial domain.
smesh - a Delaunay triangulation of the spatial domain returned by INLA::inla.mesh.2d().
tmesh - optional, a temporal mesh returned by INLA::inla.mesh.1d()).
parameters - a vector of named starting values for \(\boldsymbol{\beta}\) (beta), | \(\text{log}(\tau)\) (log_tau), \(\text{log}(\kappa)\) (log_kappa), and \(\textrm{arctan}(\rho)\) (atanh_rho, optional).
fit_mlgcp()
locs, sf, and smesh - as fit_lgcp().
marks - a matrix of marks for each observation of the point pattern.
parameters - a list of named parameters, as fit_lgcp() plus (betamarks), (betapp), (marks_coefs_pp ).
strfixed - fixed structural parameters, depends on mark distribution.
fields - a binary vector indicating whether there is a new random field for each mark.
fit_stelfi()
times - as fit_hawkes().
locs, sf, and smesh - as fit_lgcp().
parameters - a list of named parameter starting values for \(\mu\) (mu), \(\alpha\) (alpha), \(\beta\) (beta), \(\sigma_x\) (xsigma) \(\sigma_y\) (ysigma), and \(\rho\) (rho).
GMRF - logical, should a GMRF be included as a latent spatial effect if so \(\tau\) (tau) and \(\kappa\)(kappa) supplied to parameters.
Summary of utility and simulation functions listing the key arguments for each.
Function
Key arguments
Purpose
get_coefs()
obj - a fitted model object returned by any one of the functions in the Table above
Extract estimated parameter values from a fitted model.
get_fields()
As fit_lgcp() and
sd - logical, return standard deviation.
Extract estimated mean, or standard deviation, of GMRF(s).
get_weights()
mesh - a Delaunay triangulation of the spatial domain returned by INLA::inla.mesh. 2d().
sf - a polygon of the spatial domain.
Calculate mesh weights.
mesh_2_sf()
mesh - a Delaunay triangulation of the spatial domain returned by INLA::inla.mesh. 2d().
Transforms mesh into a sf object.
show_field()
x - a vector of values, one per each smesh node.
smesh - as fit_lgcp() .
sf - as fit_lgcp().
clip - logical, clip to domain
Plots spatial random field values.
show_hawkes()
obj - a fitted model object returned by fit_hawkes() or fit_hawkes_cbf().