Package index • SDALGCP2

Fitting

The main interface and its controls.

Lower-level fitters used by sdalgcp() for specific settings.

SDALGCP2(): Fit a spatial SDA-LGCP model
SDALGCP2_raster(): Fit an SDA-LGCP with spatially continuous (raster) covariates
SDALGCP2_misaligned(): Fit an SDA-LGCP with covariates measured on a different support
SDALGCP2_ST(): Fit a spatio-temporal SDA-LGCP model (Kronecker-free)
mcml_fit(): Monte Carlo maximum likelihood estimation for the spatial SDA-LGCP

Discretisation and the aggregated correlation assembly.

sda_points(): Generate candidate sampling points inside each region
precompute_corr(): Precompute aggregated region-level correlation matrices

control_mcmc(): MCMC control settings for the MALA sampler
laplace_sampling(): Sample the latent field [S | Y] (Poisson, non-nested) via C++ MALA

predict(<sdalgcp>): Predict relative risk from an sdalgcp fit
predict(<SDALGCP2>): Predict relative risk from a fitted SDALGCP2 model
predict(<SDALGCP2_ST>): Discrete (region x time) prediction for a spatio-temporal fit
exceedance(): Exceedance probabilities P(risk > threshold)

Maps and post-fit graphics.

plot(<sdalgcp>): Map an sdalgcp fit
plot(<SDALGCP2_pred>): Map a fitted SDALGCP2 prediction
plot(<SDALGCP2_ST_pred>): Map a spatio-temporal prediction for one time
plot(<SDALGCP2>): Plot an SDALGCP2 fit (the phi profile deviance)
map_exceedance(): Map exceedance probabilities P(risk > threshold)
phi_profile(): Profile likelihood and confidence interval for the spatial scale phi
coef_plot(): Coefficient plot of fixed effects (and sigma^2) with confidence intervals
report(): One-call panel of post-fit graphics