Index of values

calc model ~targets

calc inputs ~sigma2

calc inducing points

calc kernel inducing_points

calc ?predictive mean variance

calc ?predictive mean variance

calc co_variance_predictor ~sigma2 inputs

calc co_variance_predictor ~sigma2 inputs

calc co_variance_predictor ~sigma2 input

calc kernel inducing_points co_variance_coeffs

calc mean_predictor inputs

calc mean_predictor input

calc inducing_points ~coeffs

calc trained

calc model ~targets

calc inputs ~sigma2

create points inducing

calc inducing point

calc kernel inducing_points

calc_co_variance_coeffs model

calc_cross kernel ~inputs ~inducing

calc_deriv_cross cross hyper

calc_deriv_diag diag hyper

calc_deriv_upper upper hyper

calc_diag kernel inputs

calc_eval trained

calc_eval model

calc_eval inputs

calc_eval inducing

calc_log_evidence hyper_t hyper

calc_log_evidence hyper_t hyper

calc_log_evidence trained

calc_log_evidence model

calc_log_evidence_sigma2 trained

calc_log_evidence_sigma2 model

calc_mad trained

calc_mad trained

calc_mean_coeffs trained

calc_model model

calc_model_inputs model

calc_model_inputs model

calc_mse trained

calc_msll trained

calc_n_samples trained

calc_sse trained

calc_shared_cross kernel ~inputs ~inducing

calc_shared_diag kernel inputs

calc_shared_upper kernel inducing

calc_smse trained

calc_sse trained

calc_target_variance trained

calc_trained trained

calc_upper kernel inputs

calc_upper kernel inducing

check_deriv_hyper ?eps ?tol kernel inducing_points points hyper will raise Failure if the derivative code provided in the specification of the covariance function given parameter hyper, the kernel, inducing_points and input points exceeds the tolerance tol when compared to finite differences using epsilon eps.

choose_n_first_inputs kernel inputs ~n_inducing

choose_n_random_inputs ?rnd_state kernel inputs ~n_inducing

choose_subset inputs indexes

copy bm

create mats

create inputs

create params

create_default_kernel points

create_default_kernel_params inputs ~n_inducing

create_inducing kernel inputs

eval kernel input inducing

eval_one kernel point

get ?predictive covariances

get ?predictive variances

get ?predictive variance

get means

get mean

get_all kernel inducing inputs

get_coeffs mean_predictor

get_inducing mean_predictor

get_inputs model

get_inputs model

get_kernel model

get_model trained

get_n_points inputs

get_n_points inducing

get_params kernel

get_points kernel inputs

get_points kernel inducing

get_sigma2 model

get_targets trained

get_value kernel inducing inputs hyper

get_variances covariances

potrf ?jitter bm perform Cholesky factorization on block diagonal matrix bm using Cholesky jitter if given.

potri ?jitter ?factorize bm invert block diagonal matrix bm using its Cholesky factor.

prepare_hyper trained

prepare_hyper model

sample ?rng sampler

sample ?rng sampler

samples ?rng sampler ~n

samples ?rng sampler ~n

self_test ?eps ?tol kernel inducing_points points ~sigma2 ~targets hyper will raise Failure if the internal derivative code for the log evidence given parameter hyper, the kernel, inducing_points, input points, noise level sigma2 and targets exceeds the tolerance tol when compared to finite differences using epsilon eps.

set_values kernel inducing inputs hypers values

train ?step ?tol ?epsabs ?report_trained_model ?report_gradient_norm ?kernel ?sigma2 ?inducing ?n_rand_inducing ?learn_sigma2 ?hypers ~inputs ~targets () takes the optional initial optimizer step size step, the optimizer line search tolerance tol, the minimum gradient norm epsabs to achieve by the optimizer, callbacks for reporting intermediate results report_trained_model and report_gradient_norm, an optional kernel, noise level sigma2, inducing inputs inducing, number of randomly chosen inducing inputs n_rand_inducing, a flag for whether the noise level should be learnt learn_sigma2, an array of optional hyper parameters hypers which should be optimized, and the inputs and targets.

update_sigma2 model sigma2

update_sigma2 model sigma2

weighted_eval kernel ~inputs ~inducing ~coeffs

weighted_eval kernel input inducing ~coeffs