hdBIC {DisaggregateTS} | R Documentation |
High-dimensional BIC score
Description
This function calculates a BIC score that performs better than the 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 (an |
Y |
Low-frequency response vector that has been GLS rotated (an |
covariance |
Aggregated AR covariance matrix (an |
beta |
Estimate of the regression coefficients (a |
Value
The BIC score for model comparison.
References
Yu G, Bien J (2019). “Estimating the error variance in a high-dimensional linear model.” Biometrika, 106(3), 533–546.
[Package DisaggregateTS version 3.0.1 Index]