NRRR.ini: Generate initial estimators

In xliu-stat/NRRR: Multivariate Functional Regression via Nested Reduced-Rank Regularization

Description

This function provides the initial estimators of U and V to initialize the blockwise coordinate descent algorithm.

Usage

NRRR.ini(Y, X, r, rx, ry, jx, jy, p, d, n)

Arguments

Y	response matrix of dimension n-by-jy*d.
X	design matrix of dimension n-by-jx*p.
r	rank of the local reduced-rank structure.
rx	number of latent predictors.
ry	number of latent responses.
jx	number of basis functions to expand the functional predictor.
jy	number of basis functions to expand the functional response.
p	number of predictors.
d	number of responses.
n	sample size.

Value

The function returns a list:

Ag	the estimated U.
Bg	the estimated V.

References

Liu, X., Ma, S., & Chen, K. (2020). Multivariate Functional Regression via Nested Reduced-Rank Regularization. arXiv: Methodology.

Examples

library(NRRR)
simDat <- NRRR.sim(n = 100, ns = 200, nt = 200, r = 5, rx = 3, ry = 3,
                   jx = 15, jy = 15, p = 10, d = 6, s2n = 1, rho_X = 0.5,
                   rho_E = 0, Sigma = "CorrAR")
fit_init <- with(simDat, NRRR.ini(Y = Yest, X = Xest, r = 5,
                 rx = 3, ry = 3, jx = 15, jy = 15,
                 p = 10, d = 6, n = 100))
fit_init$Ag

xliu-stat/NRRR documentation built on Jan. 9, 2021, 3:23 p.m.