predict.dsda: Prediction for direct sparse discriminant analysis

In TULIP: A Toolbox for Linear Discriminant Analysis with Penalties

Description

Predict the class labels by direct sparse discriminant analysis.

Usage

## S3 method for class 'dsda'
predict(object, newx, z=NULL, ztest=NULL, gamma=NULL,...)

Arguments

object	An object returned by dsda or msda with binary setting.
newx	An n by p matrix containing the predictors.
z	Input training covariates matrix. z can be omitted if there is no covariate.
ztest	Input testing covariates matrix. ztest can be omitted if there is no covariate.
gamma	Coefficients of covariates obtained from adjvec. gamma is NULL if there is no covariate.
...	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, dsda.all, predict.msda

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