Package: NeuralEstimators 0.1.1

NeuralEstimators: Likelihood-Free Parameter Estimation using Neural Networks

An 'R' interface to the 'Julia' package 'NeuralEstimators.jl'. The package facilitates the user-friendly development of neural point estimators, which are neural networks that map data to a point summary of the posterior distribution. These estimators are likelihood-free and amortised, in the sense that, after an initial setup cost, inference from observed data can be made in a fraction of the time required by conventional approaches; see Sainsbury-Dale, Zammit-Mangion, and Huser (2024) <doi:10.1080/00031305.2023.2249522> for further details and an accessible introduction. The package also enables the construction of neural networks that approximate the likelihood-to-evidence ratio in an amortised manner, allowing one to perform inference based on the likelihood function or the entire posterior distribution; see Zammit-Mangion, Sainsbury-Dale, and Huser (2024, Sec. 5.2) <doi:10.48550/arXiv.2404.12484>, and the references therein. The package accommodates any model for which simulation is feasible by allowing the user to implicitly define their model through simulated data.

Authors:Matthew Sainsbury-Dale [aut, cre]

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NeuralEstimators.pdf |NeuralEstimators.html
NeuralEstimators/json (API)

# Install 'NeuralEstimators' in R:
install.packages('NeuralEstimators', repos = c('https://mattsainsburydale.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

3.30 score 1 scripts 156 downloads 18 exports 2 dependencies

Last updated 3 days agofrom:9ca523b8d1. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 04 2024
R-4.5-winOKNov 04 2024
R-4.5-linuxOKNov 04 2024
R-4.4-winOKNov 04 2024
R-4.4-macOKNov 04 2024
R-4.3-winOKNov 04 2024
R-4.3-macOKNov 04 2024

Exports:assessbiasbootstrapencodedataestimateinitialise_estimatorloadstateloadweightsmapestimatemlestimateplotdistributionplotestimatesriskrmsesampleposteriorsavestatetanhlosstrain

Dependencies:JuliaConnectoRmagrittr

Introduction to NeuralEstimators

Rendered fromNeuralEstimators.html.asisusingR.rsp::asison Nov 04 2024.

Last update: 2024-11-03
Started: 2024-11-03

NeuralEstimators with Incomplete Gridded Data

Rendered fromNeuralEstimators_IncompleteData.html.asisusingR.rsp::asison Nov 04 2024.

Last update: 2024-11-03
Started: 2024-11-03