fmou-class {FastGaSP} | R Documentation |
FMOU class
Description
An S4 class for fast parameter estimation in the FMOU model, a latent factor model with a fixed or estimated orthogonal factor loading matrix, where each latent factor is modeled as an O-U (Ornstein-Uhlenbeck) process.
Objects from the Class
Objects of this class are created and initialized using the fmou
function to set up the estimation.
Slots
output
:object of class
matrix
. The observation matrix.d
object of class
integer
to specify the number of latent factors.est_d
object of class
logical
, default isFALSE
. IfTRUE
, d will be estimated by either variance matching (when noise level is given) or information criteria (when noise level is unknown). Otherwise, d is fixed, and users must assign a value tod
.est_U0
object of class
logical
, default isTRUE
. IfTRUE
, the factor loading matrix (U0) will be estimated. Otherwise, U0 is fixed.est_sigma0_2
object of class
logical
, default isTRUE
. IfTRUE
, the variance of the noise will be estimated. Otherwise, it is fixed.U0
object of class
matrix
. The fixed factor loading matrix. Users should assign a k*d matrix to it whenest_U0=False
. Here k is the length of observations at each time step.sigma0_2
object of class
numeric
. Variance of noise. User should assign a value to it whenest_sigma0_2=False
.
Methods
- fit.fmou
See
fit.fmou
.- predict.fmou
See
predict.fmou
.
Author(s)
Mengyang Gu [aut, cre], Xinyi Fang [aut], Yizi Lin [aut]
Maintainer: Mengyang Gu <mengyang@pstat.ucsb.edu>
References
Lin, Y., Liu, X., Segall, P., & Gu, M. (2025). Fast data inversion for high-dimensional dynamical systems from noisy measurements. arXiv preprint arXiv:2501.01324.
See Also
fmou
for more details about how to create a fmou
object.