sampleposterior

Samples from the approximate posterior distribution given data <code>Z</code>.

An 'R' interface to the 'Julia' package 'NeuralEstimators.jl'. The package facilitates the user-friendly development of neural Bayes estimators, which are neural networks that map data to a point summary of the posterior distribution (Sainsbury-Dale et al., 2024, <doi:10.1080/00031305.2023.2249522>). These estimators are likelihood-free and amortised, in the sense that, once the neural networks are trained on simulated data, inference from observed data can be made in a fraction of the time required by conventional approaches. The package also supports amortised Bayesian or frequentist inference using neural networks that approximate the posterior or likelihood-to-evidence ratio (Zammit-Mangion et al., 2025, Sec. 3.2, 5.2, <doi:10.48550/arXiv.2404.12484>). The package accommodates any model for which simulation is feasible by allowing users to define models implicitly through simulated data.

Matthew Sainsbury-Dale

NeuralEstimators

Likelihood-Free Parameter Estimation using Neural Networks

sampleposterior function

<dl><dt>estimator</dt>
<dd>a neural posterior or likelihood-to-evidence-ratio estimator</dd>
<dt>Z</dt>
<dd>data in a format amenable to the neural-network architecture of <code>estimator</code></dd>
<dt>N</dt>
<dd>number of approximate posterior samples to draw</dd>
<dt>...</dt>
<dd>additional keyword arguments passed to the Julia version of <a href="https://msainsburydale.github.io/NeuralEstimators.jl/dev/API/core/#NeuralEstimators.sampleposterior"><code>sampleposterior()</code></a>, applicable when <code>estimator</code> is a likelihood-to-evidence-ratio estimator</dd></dl>

Arguments

sampleposterior — sampleposterior

<dl>

<dt>estimator</dt>
<dd>a neural posterior or likelihood-to-evidence-ratio estimator</dd>


<dt>Z</dt>
<dd>data in a format amenable to the neural-network architecture of <code>estimator</code></dd>


<dt>N</dt>
<dd>number of approximate posterior samples to draw</dd>


<dt>...</dt>
<dd>additional keyword arguments passed to the Julia version of <a href='https://msainsburydale.github.io/NeuralEstimators.jl/dev/API/core/#NeuralEstimators.sampleposterior'><code>sampleposterior()</code></a>, applicable when <code>estimator</code> is a likelihood-to-evidence-ratio estimator</dd>

</dl>

sampleposterior: sampleposterior

Description

Usage

Value

Arguments

See Also