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factormodel  

Factor Model Estimation Using Proxy Variables
View on CRAN: Click here


Download and install factormodel package within the R console
Install from CRAN:
install.packages("factormodel")

Install from Github:
library("remotes")
install_github("cran/factormodel")

Install by package version:
library("remotes")
install_version("factormodel", "1.0")



Attach the package and use:
library("factormodel")
Maintained by
Yujung Hwang
[Scholar Profile | Author Map]
First Published: 2021-06-04
Latest Update: 2021-06-04
Description:
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) ; Hu (2008) ; Hu(2017) ). The function 'cproxyme' estimates a linear factor model (Cunha, Heckman, and Schennach (2010) ).
How to cite:
Yujung Hwang (2021). factormodel: Factor Model Estimation Using Proxy Variables. R package version 1.0, https://cran.r-project.org/web/packages/factormodel. Accessed 12 Apr. 2025.
Previous versions and publish date:
No previous versions
Other packages that cited factormodel R package
View factormodel citation profile
Other R packages that factormodel depends, imports, suggests or enhances
Complete documentation for factormodel
Functions, R codes and Examples using the factormodel R package
Some associated functions: cproxyme . dproxyme . makeDummy . weighted.cov . weighted.var . 
Some associated R codes: cproxyme.R . dproxyme.R . makeDummy.R . weighted.cov.R . weighted.var.R .  Full factormodel package functions and examples
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