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40 lines
1.3 KiB
Go
40 lines
1.3 KiB
Go
// Copyright ©2015 The gonum Authors. All rights reserved.
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// Use of this source code is governed by a BSD-style
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// license that can be found in the LICENSE file.
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package sample
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import "github.com/gonum/stat/dist"
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type ProposalDist struct {
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Sigma float64
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}
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func (p ProposalDist) ConditionalRand(y float64) float64 {
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return dist.Normal{Mu: y, Sigma: p.Sigma}.Rand()
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}
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func (p ProposalDist) ConditionalLogProb(x, y float64) float64 {
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return dist.Normal{Mu: y, Sigma: p.Sigma}.LogProb(x)
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}
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func ExampleMetropolisHastings_burnin() {
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n := 1000 // The number of samples to generate.
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burnin := 50 // Number of samples to ignore at the start.
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var initial float64
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// target is the distribution from which we would like to sample.
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target := dist.Weibull{K: 5, Lambda: 0.5}
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// proposal is the proposal distribution. Here, we are choosing
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// a tight Gaussian distribution around the current location. In
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// typical problems, if Sigma is too small, it takes a lot of samples
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// to move around the distribution. If Sigma is too large, it can be hard
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// to find acceptable samples.
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proposal := ProposalDist{Sigma: 0.2}
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samples := make([]float64, n+burnin)
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MetropolisHastings(samples, initial, target, proposal, nil)
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// Remove the initial samples through slicing.
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samples = samples[burnin:]
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}
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