Man pages for jtipton25/sgMRA
Multi-Resolution Gaussian Process Approximations with Stochastic Gradient Descent

adamADAM stochastic process update
distance_near_chunk_cppCalculate thresheld pairwise distance for a row using loops...
distance_near_loop_cppCalculate thresheld pairwise distance for a row using loops...
distance_near_row_cppCalculate thresheld pairwise distance for a row
distance_near_with_ddist_cppCalculate thresheld pairwise distance
dwendland_basisTitle
essCode for the elliptical slice sampler
eval_basisEvaluate the MRA basis
fit_nonstationary_MRATitle
fit_sgdTitle
gradient_funCalculate the Gradient for Regression
gradient_fun_miniCalculate the Gradient for Regression using minibatch
gradient_fun_penaltyCalculate the Gradient for Penalized Regression
make_gridMake the deep MRA grid
make_QGenerate CAR precision matrix
predict_deep_MRATitle
regression_gradient_descentFit a regression gradient descent
sgMRAsgMRA
sim_deep_mraSimulate deep MRA
sim_example_splinesSimulate a B-spline mixed model
target_funCalculate the Target function for Regression
update_tuningthis function updates the univariate Gaussian random walk...
update_tuning_matthis function updates a matrix block of univariate Gaussian...
update_tuning_mvthis function updates a block Gaussian random walk proposal...
update_tuning_mv_matthis function updates multiple block Gaussian random walk...
update_tuning_vecthis function updates a vector block of univariate Gaussian...
jtipton25/sgMRA documentation built on Feb. 9, 2023, 4:53 a.m.