dist_reg_mcmc()#

liesel.model.distreg.dist_reg_mcmc(model, seed, num_chains, tau2_jitter_fn=<function <lambda>>, beta_jitter_fn=<function <lambda>>)[source]#

Configures an EngineBuilder for a distributional regression model.

The EngineBuilder uses a Metropolis-in-Gibbs MCMC algorithm with an IWLSKernel for the regression coefficients and a GibbsKernel for the smoothing parameters for a distributional regression model.

Parameters:
  • model (Model) – A model built with a DistRegBuilder.

  • seed (int) – The PRNG seed for the engine builder.

  • num_chains (int) – The number of chains to be sampled.

  • tau2_jitter_fn (Callable[[Any, Any], Any]) – Jittering function for the smoothing parameters. (default: <function <lambda> at 0x7f28f3aa5510>)

  • beta_jitter_fn (Callable[[Any, Any], Any]) – Jittering function for the regression coefficients. (default: <function <lambda> at 0x7f28f29f7250>)

Return type:

EngineBuilder

See also

EngineBuilder.set_jitter_fns()

Method for setting the jittering functions