full_sc_lhood_fast: Evaluate optimized self-correcting log-likelihood

In ldmppr: Estimate and Simulate from Location Dependent Marked Point Processes

Evaluate optimized self-correcting log-likelihood

Description

Optimized implementation used by estimation workflows. Intended to be numerically consistent with full_sc_lhood().

Usage

full_sc_lhood_fast(xgrid, ygrid, tgrid, tobs, data, params, bounds)

Arguments

xgrid	NumericVector of x-grid values.
ygrid	NumericVector of y-grid values.
tgrid	NumericVector of integration-time grid values.
tobs	NumericVector of observed event times.
data	NumericMatrix with columns (time, x, y), sorted by nondecreasing time.
params	NumericVector of model parameters (alpha1, beta1, gamma1, alpha2, beta2, alpha3, beta3, gamma3).
bounds	NumericVector of integration bounds (bt, bx, by).

Value

Full self-correcting log-likelihood value.

ldmppr documentation built on March 3, 2026, 9:06 a.m.