hdBIC {TSdisaggregation} | R Documentation |
BIC score
Description
This function calculates the BIC score that has been shown to work better than ordinary BIC in high-dimensional scenarios. It uses the variance estimator given in Yu and Bien (2019).
Usage
hdBIC(X, Y, covariance, beta)
Arguments
X |
Aggregated indicator series matrix that has been GLS rotated. |
Y |
Low-frequency response vector that has been GLS rotated. |
covariance |
Aggregated AR covariance matrix. |
beta |
Estimate of beta from LARS algorithm for a certain lambda. |
References
Yu G, Bien J (2019). “Estimating the error variance in a high-dimensional linear model.” Biometrika, 106(3), 533–546.
[Package TSdisaggregation version 2.0.0 Index]