## Types in MathNet.Numerics.Statistics.Mcmc

Type UnivariateHybridMC

Namespace MathNet.Numerics.Statistics.Mcmc

Parent HybridMCGeneric<T>

A hybrid Monte Carlo sampler for univariate distributions.

### Public Constructors

#### UnivariateHybridMC(double x0, DensityLn<T> pdfLnP, int frogLeapSteps, double stepSize, int burnInterval, double pSdv)

Constructs a new Hybrid Monte Carlo sampler for a univariate probability distribution. The momentum will be sampled from a normal distribution with standard deviation specified by pSdv using the default Random random number generator. A three point estimation will be used for differentiation. This constructor will set the burn interval.
##### Parameters
###### `double` x0

The initial sample.

###### `DensityLn<T>` pdfLnP

The log density of the distribution we want to sample from.

###### `int` frogLeapSteps

Number frog leap simulation steps.

###### `double` stepSize

Size of the frog leap simulation steps.

###### `int` burnInterval

The number of iterations in between returning samples.

###### `double` pSdv

The standard deviation of the normal distribution that is used to sample the momentum.

#### UnivariateHybridMC(double x0, DensityLn<T> pdfLnP, int frogLeapSteps, double stepSize, int burnInterval, double pSdv, Random randomSource)

Constructs a new Hybrid Monte Carlo sampler for a univariate probability distribution. The momentum will be sampled from a normal distribution with standard deviation specified by pSdv using a random number generator provided by the user. A three point estimation will be used for differentiation. This constructor will set the burn interval.
##### Parameters
###### `double` x0

The initial sample.

###### `DensityLn<T>` pdfLnP

The log density of the distribution we want to sample from.

###### `int` frogLeapSteps

Number frog leap simulation steps.

###### `double` stepSize

Size of the frog leap simulation steps.

###### `int` burnInterval

The number of iterations in between returning samples.

###### `double` pSdv

The standard deviation of the normal distribution that is used to sample the momentum.

###### `Random` randomSource

Random number generator used to sample the momentum.

### Public Methods

#### doubleSample()

Returns a sample from the distribution P.

#### Double[]Sample(int n)

Returns a number of samples.
##### Parameters
###### `int` n

The number of samples we want.

##### Return
###### `Double[]`

An array of samples.

### Public Properties

#### doubleMomentumStdDev get; set;

Gets or sets the standard deviation used in the sampling of the momentum.