refitME
Measurement Error Modelling using MCEM
Fits measurement error models using Monte Carlo Expectation Maximization (MCEM). For specific details on the methodology, see: Greg C. G. Wei & Martin A. Tanner (1990) A Monte Carlo Implementation of the EM Algorithm and the Poor Man's Data Augmentation Algorithms, Journal of the American Statistical Association, 85:411, 699-704 <doi:10.1080/01621459.1990.10474930> For more examples on measurement error modelling using MCEM, see the 'RMarkdown' vignette: "'refitME' R-package tutorial".
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.3.1 |
rolling linux/jammy R-4.5 | refitME_1.3.1.tar.gz |
1.9 MiB |
1.3.1 |
rolling linux/noble R-4.5 | refitME_1.3.1.tar.gz |
1.9 MiB |
1.3.1 |
rolling source/ R- | refitME_1.3.1.tar.gz |
1.4 MiB |
1.3.1 |
latest linux/jammy R-4.5 | refitME_1.3.1.tar.gz |
1.9 MiB |
1.3.1 |
latest linux/noble R-4.5 | refitME_1.3.1.tar.gz |
1.9 MiB |
1.3.1 |
latest source/ R- | refitME_1.3.1.tar.gz |
1.4 MiB |
1.3.1 |
2026-04-26 source/ R- | refitME_1.3.1.tar.gz |
1.4 MiB |
1.3.1 |
2026-04-23 source/ R- | refitME_1.3.1.tar.gz |
1.4 MiB |
1.3.1 |
2026-04-09 windows/windows R-4.5 | refitME_1.3.1.zip |
1.9 MiB |
1.3.1 |
2025-04-20 source/ R- | refitME_1.3.1.tar.gz |
1.4 MiB |