SF.DR: Directional regression for sufficient forecasting

In sufficientForecasting: Sufficient Forecasting using Factor Models

Directional regression for sufficient forecasting

Description

Directional regression for sufficient forecasting

Usage

SF.DR(y, X, newX = NULL, K = "default", L = 1, etaopg = "default", nslices = 3)

Arguments

y	Response, T by 1 matrix
X	Predictors, p by T matrix
newX	New predictors, a vector contains p entries (or NULL)
K	The number of common factors (default = obtained by getK)
L	The number of predictive indices, L is required to be no greater than K (default = 1)
etaopg	hyperparameter in DR (default = obtained by opg)
nslices	hyperparameter in DR (default = 3)

Value

Out-of-sample forecast for newX; or in-sample forecast for the last observed data point if newX is NULL

References

Luo, W., Xue, L., Yao, J. and Yu, X. (2022), Inverse moment methods for sufficient forecasting using high-dimensional predictors, Biometrika 109(2), 473–487.

Examples

utils::data(dataExample,package = "sufficientForecasting")
SF.DR(dataExample$y,dataExample$X,dataExample$newX)

sufficientForecasting documentation built on March 7, 2023, 6:13 p.m.