gene: Simulated gene data to predict weight loss

In ChubingZeng/classo: Regularized Regression with Differential Penalties Integrating External Information

Description

The simulated gene data contains 50 observations, 200 predictors, and an continuous outcome, bone mineral density. The external information Z is four previous study results that identifies the biological importance of genes.

Usage

data(gene)

Format

The gene object is a list containing three elements:

• GeneExpression: Matrix of gene expression predictors.

• bonedensity: Continuous outcome variable

• PreviousStudy: Whether each gene is identified by previous study results.

See Also

diet

Examples

data(gene)
X <- gene$geneItems
Y <- gene$weightloss
Z <- gene$NuitritionFact
fit <- xtune(X,Y,Z)
fit$penalty.vector

ChubingZeng/classo documentation built on June 4, 2019, 12:37 p.m.