Package: NeuralEstimators
Title: Likelihood-Free Parameter Estimation using Neural Networks
Version: 0.2.2
Authors@R: 
    person(given = "Matthew",
           family = "Sainsbury-Dale",
           role = c("aut", "cre"),
           email = "msainsburydale@gmail.com")
Description: 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.
Maintainer: Matthew Sainsbury-Dale <msainsburydale@gmail.com>
License: GPL (>= 2)
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.2
Imports: JuliaConnectoR, magrittr
Suggests: dplyr, ggplot2, ggplotify, ggpubr, gridExtra, knitr,
        rmarkdown, markdown, R.rsp, testthat (>= 3.0.0)
Config/testthat/edition: 3
SystemRequirements: Julia (>= 1.11)
VignetteBuilder: R.rsp
URL: https://github.com/msainsburydale/NeuralEstimators,
        https://msainsburydale.github.io/NeuralEstimators.jl/dev/
Repository: https://msainsburydale.r-universe.dev
Date/Publication: 2026-09-08 08:09:10 UTC
RemoteUrl: https://github.com/msainsburydale/neuralestimators
RemoteRef: HEAD
RemoteSha: 26f973f6b8fa0b650b6329388e911569be78f73d
NeedsCompilation: no
Packaged: 2026-10-08 10:49:21 UTC; root
Author: Matthew Sainsbury-Dale [aut, cre]