abc.factor.number: Factor number estimator of Alessi, Barigozzi and Capasso...

In fnets: Factor-Adjusted Network Estimation and Forecasting for High-Dimensional Time Series

Factor number estimator of Alessi, Barigozzi and Capasso (2010)

Description

Estimates the number of factors by minimising an information criterion over sub-samples of the data. Currently the three information criteria proposed in Alessi, Barigozzi and Capasso (2010) (ic.op = 1, 2, 3) and their variations with logarithm taken on the cost (ic.op = 4, 5, 6) are implemented, with ic.op = 5 recommended as a default choice based on numerical experiments.

Usage

abc.factor.number(x, covx = NULL, q.max = NULL, center = TRUE)

Arguments

x	input time series matrix, with each row representing a variable
covx	covariance of x
q.max	maximum number of factors; if q.max = NULL, a default value is selected as min(50, floor(sqrt(min(dim(x)[2] - 1, dim(x)[1]))))
center	whether to de-mean the input x row-wise

Details

See Alessi, Barigozzi and Capasso (2010) for further details.

Value

a list containing

q.hat

the mimimiser of the chosen information criteria

References

Alessi, L., Barigozzi, M., & Capasso, M. (2010) Improved penalization for determining the number of factors in approximate factor models. Statistics & Probability Letters, 80(23-24):1806–1813.

fnets documentation built on May 29, 2024, 8:42 a.m.