CP: Circularly Projected Estimation

In GrFA: Group Factor Analysis

Circularly Projected Estimation

Description

Circularly Projected Estimation for Group Factor Model.

Usage

CP(y, rmax = 8, r0 = NULL, r = NULL, localfactor = FALSE, type = "IC3")

Arguments

y	A list of the observation data, each element is a data matrix of each group with dimension T \times N_m.
rmax	The maximum factor numbers of all groups. Default is 8.
r0	The number of global factors. Default is NULL, the algorithm will automatically estimate the number of global factors. If you have prior information about the true number of global factors, you can set it manually.
r	The number of local factors in each group. Default is NULL, the algorithm will automatically estimate the number of local factors. If you have prior information, set it manually as an integer vector of length M (the number of groups).
localfactor	Logical. If FALSE (default), local factors are not estimated. If TRUE, local factors will be estimated.
type	The method used in estimating the local factor numbers in each group after projecting out the global factors. Default is "IC3".

Value

An object of class "GFA" containing:

r0hat	The estimated number of global factors.
rhat	The estimated number of local factors (if localfactor = TRUE).
rho	The eigenvalues of the circular projection matrix.
Ghat	The estimated global factors.
Fhat	The estimated local factors (if localfactor = TRUE).
loading_G	A list consisting of the estimated global factor loadings.
loading_F	A list consisting of the estimated local factor loadings (if localfactor = TRUE).
residual	A list consisting of the residuals (if localfactor = TRUE).

References

Chen, M. (2023). Circularly Projected Common Factors for Grouped Data. Journal of Business & Economic Statistics, 41(2), 636-649.

Examples

dat <- GrFA::gendata()
CP(dat$y, rmax = 8, localfactor = TRUE)

GrFA documentation built on Dec. 7, 2025, 1:07 a.m.