dist

package

v0.3.0 Latest Latest Go to latest Published: Mar 19, 2019 License: MIT Imports: 3 Imported by: 7

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Repository

bitbucket.org/dtolpin/infergo

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Documentation ¶

Overview ¶

Package dist provides differentiatable distribution models. The package is automatically differentiated by deriv during build.

Constants ¶

This section is empty.

Variables ¶

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var Beta beta

Beta distribution, singleton instance.

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var Expon expon

Exponential distribution, singleton instance.

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var Gamma gamma

Gamma distribution, singleton instance.

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var Normal normal

Normal distribution, singleton instance.

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var SoftMax func(x, p []float64)

Outside of differentiated context, SoftMax can be used without distribution.

Functions ¶

This section is empty.

Types ¶

type Dirichlet ¶

type Dirichlet struct {
	N int // number of dimensions
}

Dirichlet distribution

func (Dirichlet) Logp ¶

func (dist Dirichlet) Logp(alpha []float64, y []float64) float64

Logp computes logpdf of a single observation.

func (Dirichlet) Logps ¶

func (dist Dirichlet) Logps(alpha []float64, y ...[]float64) float64

Logps computes logpdf of a vector of observations.

func (Dirichlet) Observe ¶

func (dist Dirichlet) Observe(x []float64) float64

Observe implements the Model interface. The parameters are alpha and observations, flattened.

func (Dirichlet) SoftMax ¶

func (dist Dirichlet) SoftMax(x, p []float64)

SoftMax transforms unconstrained parameters to a point on the unit hyperplane suitable to be observed from Dirichlet. x is the original vector, p is a point on the unit hyperplane.

Source Files ¶

View all Source files

dist.go

Directories ¶

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