A Penalized Likelihood Method for Classification With Matrix-Valued Predictors
A Penalized Likelihood Method for Classification With Matrix-Valued Predictors
We propose a penalized likelihood method to fit the linear discriminant analysis model when the predictor is matrix valued. We simultaneously estimate the means and the precision matrix, which we assume has a Kronecker product decomposition. Our penalties encourage pairs of response category mean matrix estimators to have equal entries …