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esaBcv  

Estimate Number of Latent Factors and Factor Matrix for Factor Analysis
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("esaBcv", "1.2.1.1")



Attach the package and use:
library("esaBcv")
Maintained by
Jingshu Wang
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2015-04-08
Latest Update: 2022-06-30
Description:
These functions estimate the latent factors of a given matrix, no matter it is high-dimensional or not. It tries to first estimate the number of factors using bi-cross-validation and then estimate the latent factor matrix and the noise variances. For more information about the method, see Art B. Owen and Jingshu Wang 2015 archived article on factor model ().
How to cite:
Jingshu Wang (2015). esaBcv: Estimate Number of Latent Factors and Factor Matrix for Factor Analysis. R package version 1.2.1.1, https://cran.r-project.org/web/packages/esaBcv. Accessed 23 Apr. 2025.
Previous versions and publish date:
1.0.1 (2015-04-08 00:53), 1.1.1 (2015-04-11 07:17), 1.2.1.1 (2022-06-30 12:29), 1.2.1 (2015-05-29 08:45)
Other packages that cited esaBcv R package
View esaBcv citation profile
Other R packages that esaBcv depends, imports, suggests or enhances
Functions, R codes and Examples using the esaBcv R package
Some associated functions: ESA . EsaBcv . esaBcv_package . plot.esabcv . simdat . 
Some associated R codes: ESA_BCV.R . esaBcv-package.R . plot_esaBcv.R . simdat.R .  Full esaBcv package functions and examples
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