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Hamiltonian Monte Carlo (HMC) sampler

creates
a Hamiltonian Monte Carlo (HMC) sampler, returned as a `hmc`

= hmcSampler(`logpdf`

,`startpoint`

)`HamiltonianSampler`

object. `logpdf`

is
a function handle that evaluates the logarithm of the probability
density of the equilibrium distribution and its gradient. The column
vector `startpoint`

is the initial point from which
to start HMC sampling.

After you create the sampler, you can compute MAP (maximum-a-posteriori)
point estimates, tune the sampler, draw samples, and check convergence
diagnostics using the methods of the `HamiltonianSampler`

class. For an example of this workflow,
see Bayesian Linear Regression
Using Hamiltonian Monte Carlo.

specifies
additional options using one or more name-value pair arguments. Specify
name-value pair arguments after all other input arguments.`hmc`

= hmcSampler(___,`Name,Value`

)