Man pages for jtipton25/BayesMRA
Bayesian Multi-Resolution Gaussian Process Approximations
| all_sat_temps | Temperature data from satellite measurements |
| all_sim_data | Temperature data from simulation |
| BayesMRA | BayesMRA |
| calc_omega_norm | Calulate basis function normalizing constant |
| calc_W_star | Calculate normalized basis function |
| code_test | Small temperature data from simulation for testing |
| dmvn_smw | dmvn_smw_mra |
| is_integer | Check if value is an integer or integer-like |
| is_integer_matrix | Check if an integer matrix of dimension n x m |
| is_numeric | Check if a numeric value |
| is_numeric_matrix | Check if a numeric matrix of dimension n x m |
| is_numeric_vector | Check if a numeric vector of length n |
| is_numeric_vector_with_na | Check if a numeric vector of length n with NA values allowed |
| is_numeric_with_na | Check if a numeric value with NA values allowed |
| is_positive_integer | Check if value is a positive integer or integer-like |
| is_positive_numeric | Check if a positive numeric value |
| is_sympd_matrix | Check if a symmetric positive definite numeric matrix of... |
| make_basis | Generate the basis function expansion |
| make_constraint | Construct the constraint matrices for the spatial random... |
| make_Q_alpha_2d | Generate CAR precision matrix |
| make_Q_alpha_tau2 | Title |
| mcmc_mra | Bayesian Multi-resolution Spatial Regression |
| mcmc_mra_integrated | Bayesian Multi-resolution Spatial Regression |
| mcmc_mra_vecchia | Bayesian Multi-resolution Spatial Regression |
| mra_wendland_2d | Code to construct the mutli-resolution sparse basis function... |
| mra_wendland_2d_pred | Code to construct the mutli-resolution sparse basis function... |
| partition_observations | Partition observations into MRA grid |
| plot_fitted_alphas | Plot the observed and "true" (holdout) spatial data |
| plot_fitted_MRA | Plot the fitted MRA process |
| plot_fitted_process | Plot the observed and "true" (holdout) spatial data |
| plot_MRA_grid | Plot the MRA spatial grid |
| plot_posterior_params | Posterior distribution plots from the output of 'mcmc_mra()'... |
| plot_predicted_process | Plot the observed (or true) and predicted spatial data |
| plot_sim_vs_fitted | Plot the fitted model parameters vs. simulated model... |
| plot_sparse_matrix | Plot the sparsity structure of a spam matrix object using... |
| plot_test_data | Plot the observed and "true" (holdout) spatial data |
| plot_trace | Trace plots from the output of 'mcmc_mra()' or... |
| plot_trace_alpha | Trace plots from the output of 'mcmc_mra()' or... |
| predict_mra | Predict for new data using the MRA model |
| recover_alpha | Recover the latent spatial parameters alpha |
| rmvn_arma | A function for sampling from conditional multivariate normal... |
| rmvn_arma_chol | A function for sampling from conditional multivariate normal... |
| rmvn_arma_scalar | A function for sampling from conditional multivariate normal... |
| unscale_beta | Transform the beta parameters to restore the parameters to... |
| unscale_sigma2 | Transform the sigma2 parameter to restore the parameter to... |
| update_tuning | this function updates the univariate Gaussian random walk... |
| update_tuning_mat | this function updates a matrix block of univariate Gaussian... |
| update_tuning_mv | this function updates a block Gaussian random walk proposal... |
| update_tuning_mv_mat | this function updates multiple block Gaussian random walk... |
| update_tuning_vec | this function updates a vector block of univariate Gaussian... |
| wendland_basis | calculate the Wendland basis function |
