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:Yujung Hwang [aut, cre]

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-4.5-any)factormodel_1.0.tgz(r-4.4-any)factormodel_1.0.tgz(r-4.3-any)
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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

On CRAN:

Conda:

4.78 score 4 stars 1 packages 4 scripts 222 downloads 5 exports 19 dependencies

Last updated 4 years agofrom:1f3f0fc544. Checks:1 OK, 8 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 21 2025
R-4.5-winNOTEMar 21 2025
R-4.5-macNOTEMar 21 2025
R-4.5-linuxNOTEMar 21 2025
R-4.4-winNOTEMar 21 2025
R-4.4-macNOTEMar 21 2025
R-4.4-linuxNOTEMar 21 2025
R-4.3-winNOTEMar 21 2025
R-4.3-macNOTEMar 21 2025

Exports:cproxymedproxymemakeDummyweighted.covweighted.var

Dependencies:clidplyrfansigenericsgluegtoolslifecyclemagrittrnnetpillarpkgconfigpracmaR6rlangtibbletidyselectutf8vctrswithr

factormodel

Rendered fromfactormodel.Rmdusingknitr::rmarkdownon Mar 21 2025.

Last update: 2021-04-14
Started: 2021-03-14

Readme and manuals

Help Manual

Help pageTopics
cproxymecproxyme
dproxymedproxyme
makeDummymakeDummy
weighted.covweighted.cov
weighted.varweighted.var