Bayesian Wombling using 'nimble'

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Documentation for package ‘nimblewomble’ version 0.1.0

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curvatures_gaussian Posterior samples of rates of change (gradients and curvatures) for the Matern kernel with nu\toInf producing the squared exponential kernel.
curvatures_matern2 Posterior samples of rates of change (gradients and curvatures) for the Matern kernel with nu=5/2
gamma1.mcov1 Cross-covariance terms for the posterior distribution of wombling measures for Matern nu=3/2.
gamma1n2.gauss Cross-covariance terms for the posterior distribution of wombling measures for Matern nu\toInf, the squared exponential kernel.
gamma1n2.mcov2 Cross-covariance terms for the posterior distribution of wombling measures for Matern nu=5/2, the squared exponential kernel.
gamma_int Incomplete Gamma Function
gaussian Squared Exponential Covariance kernel
gp_fit Fit a Gaussian process
gradients_matern1 Posterior samples of rates of change (gradients) for the Matern kernel with nu=3/2
materncov1 Matern Covariance kernel with nu = 3/2
materncov2 Matern Covariance kernel with nu = 5/2
pnorm_nimble Computes the Cumulative Distribution Function (CDF) for the standard Gaussian probability distribution
significance Determines significance for posterior estimates
sprates Posterior samples for rates of change
spwombling Posterior samples for wombling measures
sp_ggplot Spatial Plot Function
wombling_gaussian Posterior samples for wombling measures for the squared exponential kernel
wombling_matern1 Posterior samples for wombling measures from the Matern kernel with nu=3/2
wombling_matern2 Posterior samples for wombling measures from the Matern kernel with nu=5/2
zbeta_gaussian Posterior samples of spatial effects and intercept for the squared exponential kernel
zbeta_matern1 Posterior samples of spatial effects and intercept for the Matern kernel with nu=3/2
zbeta_matern2 Posterior samples of spatial effects and intercept for the Matern kernel with nu=5/2
zbeta_samples Posterior samples of spatial effects and intercept for Matern with nu=3/2
zXbeta Posterior samples of spatial effects and intercept for all kernels in the presence of covariates