fa.em: Factor analysis via EM algorithm to maximize likelihood
In cate: High Dimensional Factor Analysis and Confounder Adjusted Testing and Estimation
Description
Usage
Arguments
References
See Also
View source: R/factor_functions.R
Description
Factor analysis via EM algorithm to maximize likelihood
Usage
1
fa.em(Y, r, tol = 1e-06, maxiter = 1000)
Arguments
Y
data matrix, a n*p matrix
r
number of factors
tol
a tolerance scale of change of log-likelihood for convergence in the EM iterations
maxiter
maximum iterations
References
Bai, J. and Li, K. (2012). Statistical analysis of factor models of high dimension. The Annals of Statistics 40, 436-465.
See Also
factor.analysis for the main function.
cate documentation built on July 2, 2020, 4:08 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Description Usage Arguments References See Also
View source: R/factor_functions.R
Description
Factor analysis via EM algorithm to maximize likelihood
Usage
1 | fa.em(Y, r, tol = 1e-06, maxiter = 1000)
|
Arguments
Y |
data matrix, a n*p matrix |
r |
number of factors |
tol |
a tolerance scale of change of log-likelihood for convergence in the EM iterations |
maxiter |
maximum iterations |
References
Bai, J. and Li, K. (2012). Statistical analysis of factor models of high dimension. The Annals of Statistics 40, 436-465.
See Also
factor.analysis for the main function.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.