Other packages > Find by keyword >

NeuralEstimators  

Likelihood-Free Parameter Estimation using Neural Networks
View on CRAN: Click here


Download and install NeuralEstimators package within the R console
Install from CRAN:
install.packages("NeuralEstimators")

Install from Github:
library("remotes")
install_github("cran/NeuralEstimators")

Install by package version:
library("remotes")
install_version("NeuralEstimators", "0.1.0")



Attach the package and use:
library("NeuralEstimators")
Maintained by
Matthew Sainsbury-Dale
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2024-09-11
Latest Update: 2024-09-11
Description:
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.
How to cite:
Matthew Sainsbury-Dale (2024). NeuralEstimators: Likelihood-Free Parameter Estimation using Neural Networks. R package version 0.1.0, https://cran.r-project.org/web/packages/NeuralEstimators. Accessed 07 Nov. 2024.
Previous versions and publish date:
0.1.0 (2024-09-11 19:20)
Other packages that cited NeuralEstimators R package
View NeuralEstimators citation profile
Other R packages that NeuralEstimators depends, imports, suggests or enhances
Complete documentation for NeuralEstimators
Functions, R codes and Examples using the NeuralEstimators R package
Full NeuralEstimators package functions and examples
Downloads during the last 30 days
Get rewarded with contribution points by helping add
Reviews / comments / questions /suggestions ↴↴↴

Today's Hot Picks in Authors and Packages

nextGenShinyApps  
Craft Exceptional 'R Shiny' Applications and Dashboards with Novel Responsive Tools
Nove responsive tools for designing and developing 'Shiny' dashboards and applications. The scripts ...
Download / Learn more Package Citations See dependency  
con2aqi  
Calculate the AQI from Pollutant Concentration
To calculate the AQI (Air Quality Index) from pollutant concentration data. O3, PM2.5, PM10, CO, SO ...
Download / Learn more Package Citations See dependency  
robregcc  
Robust Regression with Compositional Covariates
We implement the algorithm estimating the parameters of the robust regression model with composition ...
Download / Learn more Package Citations See dependency  
bacondecomp  
Goodman-Bacon Decomposition
Decomposition for differences-in-differences with variation in treatment timing from Goodman-Bacon ...
Download / Learn more Package Citations See dependency  

23,092

R Packages

198,677

Dependencies

62,675

Author Associations

23,089

Publication Badges

© Copyright 2022 - present. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA