0    0    0    0.04   0.16   0.25

  : ***Example 4:** Optimal NOC and misclassification rate of the signal variables. The true NOC is 28. 29 is the closest value in the tested grid.*

Real data example
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The component lasso is designed for settings where the data consist of a large number of predictors which can be split into highly correlated subgroups. We use a dataset from genetics to evaluate the performance of the method, because data in this area tend to follow this structure. Molecular markers are fragments of DNA associated with certain locations in the genome. In recent years, the abundance of molecular markers has made it possible to use them to predict genetic traits using linear regression. The genetic value of genes that influence a trait of interest is defined as the average phenotypic value over individuals with that trait. A standard genetic model consists in writing the phenotype $y$ as a sum of genetic values such that $y=X\beta+\epsilon$, where $X$ contains genetic values of the considered molecular markers.\
Here, we consider the wheat data set studied in [@GYp2010]. The aim is to predict genetic values of a quantitative trait, specifically grain yield in a fixed type of 