Kernelized Stein Discrepancy for Goodness-of-Fit Tests and Stein Sampling

---

Documentation for package ‘steinsampling’ version 0.1.3

• DESCRIPTION file.

Help Pages

steinsampling-package	steinsampling: Kernelized Stein Discrepancy for Goodness-of-Fit Tests and Stein Sampling
compute_tau	Compute the FSSD feature matrix
cross_kernel	Evaluate a base kernel and its derivatives
custom_stein_kernel	Create a Stein kernel from callbacks
densitygmm	Create, sample, and evaluate a Gaussian mixture model
eval_kernel	Evaluate a base kernel and its derivatives
find_median_distance	Compute and set the squared kernel scale
fmin_grid	Optimizers for Stein Points
fmin_mc	Optimizers for Stein Points
fmin_nm	Optimizers for Stein Points
fssd_grad_kernel	Compute objective gradients for one FSSD test location
fssd_null_pvalue	FSSD statistic and its null calibration
fssd_opt_test	FSSD test with optimized test locations
fssd_rand_test	FSSD test with random test locations
fssd_statistic	FSSD statistic and its null calibration
fssd_test	Finite Set Stein Discrepancy goodness-of-fit test
get_score_evaluator	Create a score function for a fixed Gaussian mixture model
gmm	Create, sample, and evaluate a Gaussian mixture model
grad_x_kernel	Evaluate a base kernel and its derivatives
ksd_uq_matrix	Build the Stein-kernel matrix for the KSD tests
ksd_u_bootstrap	KSD-U statistic and its bootstrap
ksd_u_statistic	KSD-U statistic and its bootstrap
ksd_u_test	KSD-U goodness-of-fit test for independent observations
ksd_vq_matrix	Build the Stein-kernel matrix for the KSD tests
ksd_v_bootstrap	KSD-V statistic and its bootstrap
ksd_v_statistic	KSD-V statistic and its bootstrap
ksd_v_test	KSD-V goodness-of-fit test with wild-bootstrap calibration
mala	Markov transitions for SP-MCMC
rgmm	Create, sample, and evaluate a Gaussian mixture model
rwm	Markov transitions for SP-MCMC
scale2_kernel	Compute and set the squared kernel scale
sp_mcmc	Select Stein points from short Markov chains
sp_mcmc_eval_candidates	Select Stein points from short Markov chains
steinsampling	steinsampling: Kernelized Stein Discrepancy for Goodness-of-Fit Tests and Stein Sampling
stein_codescent	Refine Stein Points by coordinate descent
stein_kernel	Create a built-in Stein kernel
stein_kernel_imq_score	Create a score-distance IMQ Stein kernel
stein_kernel_inverse_log	Create an inverse-log Stein kernel
stein_kernel_matrix	Assemble the pairwise Stein-kernel matrix
stein_points	Construct points by Stein discrepancy minimization
stein_thinning	Select existing samples by Stein thinning
svgd	Transport particles with Stein variational gradient descent
trace_mixed_kernel	Evaluate a base kernel and its derivatives