Cross-validation of LASSO penenlty lambda.

1 2 | ```
samp1.lambda.overall(x, y, family, alpha, lambda.opt, nfolds, penalty.factor,
n.samp2, ...)
``` |

`x` |
Design matrix, of dimension n x p. |

`y` |
Vector of quantitative response variable. |

`family` |
Distribution family of |

`alpha` |
A single value n the range of 0 to 1 for the elastic net mixing parameter. |

`lambda.opt` |
Criterion for optimum selection of cross-validated lasso. Either
"lambda.1se" (default) or "lambda.min". See |

`nfolds` |
Number of folds (default is 10). See |

`penalty.factor` |
See glmnet. |

`n.samp2` |
Number of individuals in samp2 which is the max. for non zero coefficients. |

`...` |
Additional agruments. |

hit documentation built on May 30, 2017, 1:27 a.m.

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