inlamemi
Missing Data and Measurement Error Modelling in INLA
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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.1.0 |
rolling linux/jammy R-4.5 | inlamemi_1.1.0.tar.gz |
1.0 MiB |
1.1.0 |
rolling linux/noble R-4.5 | inlamemi_1.1.0.tar.gz |
1.0 MiB |
1.1.0 |
rolling source/ R- | inlamemi_1.1.0.tar.gz |
1.3 MiB |
1.1.0 |
latest source/ R- | inlamemi_1.1.0.tar.gz |
1.3 MiB |
1.1.0 |
latest linux/jammy R-4.5 | inlamemi_1.1.0.tar.gz |
1.0 MiB |
1.1.0 |
latest linux/noble R-4.5 | inlamemi_1.1.0.tar.gz |
1.0 MiB |
1.1.0 |
2026-04-26 source/ R- | inlamemi_1.1.0.tar.gz |
1.3 MiB |
1.1.0 |
2026-04-23 source/ R- | inlamemi_1.1.0.tar.gz |
1.3 MiB |
1.1.0 |
2026-04-09 windows/windows R-4.5 | inlamemi_1.1.0.zip |
1.0 MiB |
1.1.0 |
2025-04-20 source/ R- | inlamemi_1.1.0.tar.gz |
1.3 MiB |