Package: inlamemi
Type: Package
Title: Missing Data and Measurement Error Modelling in INLA
Version: 1.1.0
Authors@R: c(
  person("Emma", "Skarstein", email = "emma@skarstein.no",
         role = c("cre", "aut", "cph"), 
         comment = c(ORCID = "0000-0002-6347-855X")),
  person("Stefanie", "Muff",
         role = c("aut"),
         comment = c(ORCID = "0000-0002-8425-0757"))
  )
Description: Facilitates fitting measurement error and missing data imputation models using integrated nested Laplace approximations, according to the method described in Skarstein, Martino and Muff (2023) <doi:10.1002/bimj.202300078>. See Skarstein and Muff (2024) <doi:10.48550/arXiv.2406.08172> for details on using the package.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
VignetteBuilder: knitr
RoxygenNote: 7.3.1
Suggests: INLA, knitr, testthat (>= 3.0.0), tibble, rmarkdown, spelling
Additional_repositories: https://inla.r-inla-download.org/R/stable/
Config/testthat/edition: 3
Imports: dplyr, ggplot2, rlang, stats, methods, scales
Depends: R (>= 2.10)
URL: https://emmaskarstein.github.io/inlamemi/,
        https://github.com/emmaSkarstein/inlamemi
Language: en-US
NeedsCompilation: no
Packaged: 2024-10-31 13:42:45 UTC; emmass
Author: Emma Skarstein [cre, aut, cph]
    (<https://orcid.org/0000-0002-6347-855X>),
  Stefanie Muff [aut] (<https://orcid.org/0000-0002-8425-0757>)
Maintainer: Emma Skarstein <emma@skarstein.no>
Repository: CRAN
Date/Publication: 2024-10-31 16:10:02 UTC
Built: R 4.6.0; ; 2026-02-05 04:41:13 UTC; windows
