CP {GrFA}

Circularly Projected Estimation

Description

Circularly Projected Estimation

Usage

CP(y, rmax = 8, r0 = NULL, r = NULL, type = "BIC3")

Arguments

y

a list of the observation data, each element is a data matrix of each group with dimension T * N_m.

rmax

the maximum factor numbers of all groups.

r0

the number of global factors, default is NULL, the algorithm will automatically estimate the number of global factors. If you have the prior information about the true number of global factors, you can set it by your own.

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 the prior information about the true number of local factors, you can set it by your own, notice it should be an integer vector of length M (the number of groups).

type

the method used in estimating the local factor numbers in each group after projecting out the global factors, default is BIC3, it can also be IC3....

Value

r0hat

the estimated number of the global factors.

rho

the estimated number of the local factors.

Ghat

the estimated global factors.

Fhat

the estimated local factors.

loading_G

a list consisting of the estimated global factor loadings.

loading_F

a list consisting of the estimated local factor loadings.

e

a list consisting of the residuals.

References

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

Examples

dat = gendata()
dat
CP(dat$y)