rpca: Estimation of Approximate Factor Models
In cykbennie/fbi: Factor-Based Imputation and FRED-MD/QD Data Set
rpca R Documentation
Estimation of Approximate Factor Models
Description
rpca estimates the approximate factor models of the given matrix.
Usage
rpca(X, kmax, standardize = FALSE, tau = 0)
Arguments
X
a matrix of size T by N.
kmax
integer, indicating the maximum number of factors.
standardize
logical, indicating Whether or not X should be centered and scaled.
tau
numeric, specifying the parameter in the rank-regularized estimation.
If tau = 0, then rank regularization is not used.
Value
a list of elements:
X
kmax
standardize
tau
ic2
pc2k
pc20
Fhat
Lamhat
Chat
Sigma
IC2
PC2k
PC20
fhat
lamhat
d
d0
Author(s)
Yankang (Bennie) Chen <yankang.chen@yale.edu>
Serena Ng <serena.ng@columbia.edu>
Jushan Bai <jushan.bai@columbia.edu>
References
Jushan Bai and Serena Ng (2002), Determining the number of factors in approximate factor models.
https://doi.org/10.1111/1468-0262.00273
Jushan Bai and Serena Ng (2019), Rank regularized estimation of approximate factor models.
https://doi.org/10.1016/j.jeconom.2019.04.021
cykbennie/fbi documentation built on Jan. 24, 2025, 5:59 p.m.
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| rpca | R Documentation |
Estimation of Approximate Factor Models
Description
rpca estimates the approximate factor models of the given matrix.
Usage
rpca(X, kmax, standardize = FALSE, tau = 0)
Arguments
X |
a matrix of size T by N. |
kmax |
integer, indicating the maximum number of factors. |
standardize |
logical, indicating Whether or not X should be centered and scaled. |
tau |
numeric, specifying the parameter in the rank-regularized estimation.
If |
Value
a list of elements:
X |
|
kmax |
|
standardize |
|
tau |
|
ic2 |
|
pc2k |
|
pc20 |
|
Fhat |
|
Lamhat |
|
Chat |
|
Sigma |
|
IC2 |
|
PC2k |
|
PC20 |
|
fhat |
|
lamhat |
|
d |
|
d0 |
Author(s)
Yankang (Bennie) Chen <yankang.chen@yale.edu>
Serena Ng <serena.ng@columbia.edu>
Jushan Bai <jushan.bai@columbia.edu>
References
Jushan Bai and Serena Ng (2002), Determining the number of factors in approximate factor models. https://doi.org/10.1111/1468-0262.00273
Jushan Bai and Serena Ng (2019), Rank regularized estimation of approximate factor models. https://doi.org/10.1016/j.jeconom.2019.04.021
R Package Documentation
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We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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