Package: factormodel 1.0
factormodel: Factor Model Estimation Using Proxy Variables
Functions to estimate a factor model using discrete and continuous proxy variables. The function 'dproxyme' estimates a factor model of discrete proxy variables using an EM algorithm (Dempster, Laird, Rubin (1977) <doi:10.1111/j.2517-6161.1977.tb01600.x>; Hu (2008) <doi:10.1016/j.jeconom.2007.12.001>; Hu(2017) <doi:10.1016/j.jeconom.2017.06.002> ). The function 'cproxyme' estimates a linear factor model (Cunha, Heckman, and Schennach (2010) <doi:10.3982/ECTA6551>).
Authors:
factormodel_1.0.tar.gz
factormodel_1.0.zip(r-4.5)factormodel_1.0.zip(r-4.4)factormodel_1.0.zip(r-4.3)
factormodel_1.0.tgz(r-4.4-any)factormodel_1.0.tgz(r-4.3-any)
factormodel_1.0.tar.gz(r-4.5-noble)factormodel_1.0.tar.gz(r-4.4-noble)
factormodel_1.0.tgz(r-4.4-emscripten)factormodel_1.0.tgz(r-4.3-emscripten)
factormodel.pdf |factormodel.html✨
factormodel/json (API)
| # Install 'factormodel' in R: |
| install.packages('factormodel', repos = c('https://yujunghwang.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/yujunghwang/factormodel/issues
Last updated 3 years agofrom:1f3f0fc544. Checks:OK: 1 NOTE: 6. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 21 2024 |
| R-4.5-win | NOTE | Nov 21 2024 |
| R-4.5-linux | NOTE | Nov 21 2024 |
| R-4.4-win | NOTE | Nov 21 2024 |
| R-4.4-mac | NOTE | Nov 21 2024 |
| R-4.3-win | NOTE | Nov 21 2024 |
| R-4.3-mac | NOTE | Nov 21 2024 |
Exports:cproxymedproxymemakeDummyweighted.covweighted.var
Dependencies:clidplyrfansigenericsgluegtoolslifecyclemagrittrnnetpillarpkgconfigpracmaR6rlangtibbletidyselectutf8vctrswithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| cproxyme | cproxyme |
| dproxyme | dproxyme |
| makeDummy | makeDummy |
| weighted.cov | weighted.cov |
| weighted.var | weighted.var |
