Submitting Author
Submitting Author Name: Kyle Dewsnap
Submitting Author Github Handle:
Repository: https://github.com/kylesnap/ernest
Version submitted:1.1.0
Submission type: Stats
Badge grade: bronze
Editor: @andrewheiss
Reviewers: @tjmahr, @saudiwin

Archive: TBD
Version accepted: TBD
Language: en

• Paste the full DESCRIPTION file inside a code block below:

Package: ernest
Title: A Toolkit for Nested Sampling
Version: 1.1.0
Authors@R: 
    person("Kyle", "Dewsnap", , "kyle.dewsnap@ubc.ca", role = c("aut", "cre"),
           comment = c(ORCID = "0000-0003-2132-8083"))
Description: Bayesian evidence estimation and posterior inference with the
    nested sampling algorithm, along with S3 methods for simulating
    uncertainty and creating visualisations.
License: GPL (>= 3)
URL: https://kylesnap.github.io/ernest/
BugReports: https://github.com/kylesnap/ernest/issues/
Depends: 
    R (>= 3.5)
Imports:
    cli,
    generics,
    ggplot2,
    glue,
    lifecycle,
    matrixStats,
    posterior,
    prettyunits,
    rlang (>= 1.1.0),
    tibble,
    uniformly,
    utils,
    vctrs,
    withr
Suggests: 
    ggdist,
    knitr,
    LaplacesDemon,
    log4r,
    rmarkdown,
    testthat (>= 3.0.0),
    tidyselect,
    truncnorm,
    vdiffr,
    xml2
LinkingTo:
    cpp11,
    cpp11eigen,
    testthat
VignetteBuilder: 
    knitr
Config/testthat/edition: 3
Config/testthat/parallel: true
Config/testthat/start-first: algorithm, *_ellipsoid, mini_balls
Encoding: UTF-8
LazyData: true
Roxygen: list(markdown = TRUE, roclets = c ("namespace", "rd",
    "srr::srr_stats_roclet"))
RoxygenNote: 7.3.2

Scope

• Please indicate which of our statistical package categories this package falls under. (Please check one or more appropriate boxes below):
  Statistical Packages
  • Bayesian and Monte Carlo Routines
  • Dimensionality Reduction, Clustering, and Unsupervised Learning
  • Machine Learning
  • Regression and Supervised Learning
  • Exploratory Data Analysis (EDA) and Summary Statistics
  • Spatial Analyses
  • Time Series Analyses
  • Probability Distributions

Pre-submission Inquiry

• A pre-submission inquiry has been approved in issue#722.

General Information

• The target audience includes statisticians and researchers who use Bayesian inference and require robust estimation of model evidence and posterior distributions. ernest can be used to support Bayesian model comparison and parameter estimation, and has been built to allow users to specify their own likelihood functions and prior space specifications depending on their discipline.

• This is the first package that implements a complete toolkit for performing nested sampling in R, including an implementation of the nested sampling algorithm. Certain nested sampling implementations built for other languages do offer interfaces for R (see README). However, ernest's use of S3 generics and compatibility with popular external packages (such as ggplot2 and Stan's posterior) aim to make this package more usable and performant than non-native options.

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• I have read the author guide and I expect to maintain this package for at least 2 years or have another maintainer identified.
• I have read the Statistical Software Peer Review Guide for Authors.
• I/we have run autotest checks on the package, and ensured no tests fail.
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This package:

• does not violate the Terms of Service of any service it interacts with.
• has a CRAN and OSI accepted license.
• contains a README with instructions for installing the development version.

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