MLBC: Bias Correction Methods for Models Using Synthetic Data
Implements three bias-correction techniques (additive bias correction, multiplicative bias correction, and one-step estimation via Template Model Builder (TMB)) based on Battaglia et al. (2025 <doi:10.48550/arXiv.2402.15585>) to improve inference using synthetic data.
| Version: |
0.2.1 |
| Depends: |
R (≥ 3.5) |
| Imports: |
TMB, MASS, numDeriv, stats |
| LinkingTo: |
TMB, RcppEigen |
| Suggests: |
roxygen2 |
| Published: |
2025-06-04 |
| Author: |
Konrad Kurczynski [aut, cre],
Timothy Christensen [aut] |
| Maintainer: |
Konrad Kurczynski <konrad.kurczynski at yale.edu> |
| License: |
MIT + file LICENSE |
| NeedsCompilation: |
yes |
| Materials: |
README |
| CRAN checks: |
MLBC results |
Documentation:
Downloads:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=MLBC
to link to this page.