predict.SeSDA: Prediction for semiparametric sparse discriminant analysis

In TULIP: A Toolbox for Linear Discriminant Analysis with Penalties

Description

Predict the class labels by semiparametric sparse discriminant analysis.

Usage

## S3 method for class 'SeSDA'
predict(object, x.test,...)

Arguments

object	An object returned by SeSDA.
x.test	An n by p matrix containing the predictors.
...	Other arguments that can be passed to predict.

Value

pred	The the predicted class labels.

References

Mai, Q., Zou, H. and Yuan, M. (2013), "A direct approach to sparse discriminant analysis in ultra-high dimensions." Biometrika, 99, 29-42.

See Also

dsda, SeSDA

TULIP documentation built on Jan. 13, 2021, 3:14 p.m.