R: Proximal Hamiltonian Monte Carlo for Non-Smooth Bayesian Inference

# Proximal Hamiltonian Monte Carlo for Non-Smooth Bayesian Inference

## Documentation for package ‘pHMC’ version 0.1.0

- DESCRIPTION file.

## Help Pages

coef.phmc | S3 Methods for Proximal Hamiltonian Monte Carlo Objects
grad_my_envelope | Proximal Mapping Operators and Moreau-Yosida Envelope Gradients
logLik.phmc | S3 Methods for Proximal Hamiltonian Monte Carlo Objects
phmc | Generalized Proximal Hamiltonian Monte Carlo Sampler and Estimator
phmc_lasso | Specialized High-Level Estimators Using Proximal HMC
phmc_logistic | Specialized High-Level Estimators Using Proximal HMC
phmc_matrix | Specialized High-Level Estimators Using Proximal HMC
phmc_methods | S3 Methods for Proximal Hamiltonian Monte Carlo Objects
phmc_tune | Hyperparameter Tuning for Moreau-Yosida Regularization Parameter
plot.phmc | S3 Methods for Proximal Hamiltonian Monte Carlo Objects
print.phmc | S3 Methods for Proximal Hamiltonian Monte Carlo Objects
print.summary.phmc | S3 Methods for Proximal Hamiltonian Monte Carlo Objects
proximal_operators | Proximal Mapping Operators and Moreau-Yosida Envelope Gradients
prox_elastic_net | Proximal Mapping Operators and Moreau-Yosida Envelope Gradients
prox_l1 | Proximal Mapping Operators and Moreau-Yosida Envelope Gradients
prox_l2 | Proximal Mapping Operators and Moreau-Yosida Envelope Gradients
prox_nuclear | Proximal Mapping Operators and Moreau-Yosida Envelope Gradients
specialized_models | Specialized High-Level Estimators Using Proximal HMC
summary.phmc | S3 Methods for Proximal Hamiltonian Monte Carlo Objects
vcov.phmc | S3 Methods for Proximal Hamiltonian Monte Carlo Objects