blackjax

Subpackages

• blackjax.adaptation
  • blackjax.adaptation.base
  • blackjax.adaptation.chees_adaptation
  • blackjax.adaptation.mass_matrix
  • blackjax.adaptation.mclmc_adaptation
  • blackjax.adaptation.meads_adaptation
  • blackjax.adaptation.pathfinder_adaptation
  • blackjax.adaptation.step_size
  • blackjax.adaptation.window_adaptation
• blackjax.mcmc
  • blackjax.mcmc.barker
  • blackjax.mcmc.diffusions
  • blackjax.mcmc.dynamic_hmc
  • blackjax.mcmc.elliptical_slice
  • blackjax.mcmc.ghmc
  • blackjax.mcmc.hmc
  • blackjax.mcmc.integrators
  • blackjax.mcmc.mala
  • blackjax.mcmc.marginal_latent_gaussian
  • blackjax.mcmc.mclmc
  • blackjax.mcmc.metrics
  • blackjax.mcmc.nuts
  • blackjax.mcmc.periodic_orbital
  • blackjax.mcmc.proposal
  • blackjax.mcmc.random_walk
  • blackjax.mcmc.rmhmc
  • blackjax.mcmc.termination
  • blackjax.mcmc.trajectory
• blackjax.sgmcmc
  • blackjax.sgmcmc.csgld
  • blackjax.sgmcmc.diffusions
  • blackjax.sgmcmc.gradients
  • blackjax.sgmcmc.sghmc
  • blackjax.sgmcmc.sgld
  • blackjax.sgmcmc.sgnht
• blackjax.smc
  • blackjax.smc.tuning
    • blackjax.smc.tuning.from_kernel_info
    • blackjax.smc.tuning.from_particles
  • blackjax.smc.adaptive_tempered
  • blackjax.smc.base
  • blackjax.smc.ess
  • blackjax.smc.inner_kernel_tuning
  • blackjax.smc.resampling
  • blackjax.smc.solver
  • blackjax.smc.tempered
• blackjax.vi
  • blackjax.vi.meanfield_vi
  • blackjax.vi.pathfinder
  • blackjax.vi.schrodinger_follmer
  • blackjax.vi.svgd

Submodules

• blackjax.diagnostics

Package Contents

Functions

chees_adaptation(→ blackjax.base.AdaptationAlgorithm)	Adapt the step size and trajectory length (number of integration steps / step size)
mclmc_find_L_and_step_size(mclmc_kernel, num_steps, ...)	Finds the optimal value of the parameters for the MCLMC algorithm.
meads_adaptation(→ blackjax.base.AdaptationAlgorithm)	Adapt the parameters of the Generalized HMC algorithm.
pathfinder_adaptation(→ blackjax.base.AdaptationAlgorithm)	Adapt the value of the inverse mass matrix and step size parameters of
window_adaptation(→ blackjax.base.AdaptationAlgorithm)	Adapt the value of the inverse mass matrix and step size parameters of
ess(→ blackjax.types.Array)	Compute estimate of the effective sample size (ess).
rhat(→ blackjax.types.Array)	Gelman and Rubin (1992)'s potential scale reduction for computing multiple MCMC chain convergence.

Attributes

__version__