predict.varbvsmix: Make predictions from a model fitted by varbvsmix.

In varbvs: Large-Scale Bayesian Variable Selection Using Variational Methods

Make predictions from a model fitted by varbvsmix.

Description

This function predicts outcomes (Y) given the observed variables (X) and observed covariates (Z), and a model fitted using varbvsmix.

Usage

  ## S3 method for class 'varbvsmix'
predict(object, X, Z = NULL, ...)

Arguments

object	Output of function varbvsmix.
X	n x p input matrix, in which p is the number of variables, and n is the number of samples for which predictions will be made using the fitted model. X cannot be sparse, and cannot have any missing values (NA).
Z	n x m covariate data matrix, where m is the number of covariates. Do not supply an intercept as a covariate (i.e., a column of ones), because an intercept is automatically included in the regression model. For no covariates, set Z = NULL.
...	Other arguments to generic predict function. These extra arguments are not used here.

See Also

varbvsmix

Examples

  # See help(varbvsmix) for examples.

varbvs documentation built on June 7, 2023, 5:43 p.m.