# -------------------------------------------- # CITATION file created with {cffr} R package # See also: https://docs.ropensci.org/cffr/ # -------------------------------------------- cff-version: 1.2.0 message: 'To cite package "NeuralEstimators" in publications use:' type: software license: GPL-2.0-or-later title: 'NeuralEstimators: Likelihood-Free Parameter Estimation using Neural Networks' version: 0.1.1 doi: 10.1080/00031305.2023.2249522 identifiers: - type: doi value: 10.32614/CRAN.package.NeuralEstimators abstract: 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) 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) , 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: - family-names: Sainsbury-Dale given-names: Matthew email: msainsburydale@gmail.com preferred-citation: type: article title: Likelihood-Free Parameter Estimation with Neural Bayes Estimators authors: - name: Matthew Sainsbury-Dale - name: Andrew Zammit-Mangion - name: Raphael Huser journal: The American Statistician year: '2024' volume: '78' doi: 10.1080/00031305.2023.2249522 start: '1' end: '14' repository: https://CRAN.R-project.org/package=NeuralEstimators date-released: '2024-11-03' contact: - family-names: Sainsbury-Dale given-names: Matthew email: msainsburydale@gmail.com