Fit Bayesian Centroid MVN Small Area Estimation model using aghq.

Random effects have a multivariate Gaussian distribution with covariance matrix calculated using centroid_covariance. Kernel hyperparameters are given a prior and learnt.

Usage

ck_aghq(sf, k = 3, ii = NULL)

Arguments

sf

A simple features object with some geometry.

k

Number of quadrature points per hyperparameter dimension.

ii

The (zero-indexed) indices of the observations held-out.

Examples

ck_aghq(mw)
#> Error in sf::st_centroid(sf): object 'mw' not found