Description Usage Arguments Value

Optimize a linear regression model by coordinate descent algorithm using a covariance matrix

1 2 |

`Gamma` |
covariance matrix of explanatory variables |

`gamma` |
covariance vector of explanatory and objective variables |

`lambda` |
lambda sequence |

`R` |
matrix using exclusive penalty term |

`init_beta` |
initial values of beta |

`delta` |
ratio of regularization between l1 and exclusive penalty terms |

`maxit` |
max iteration |

`eps` |
convergence threshold for optimization |

`warm` |
warm start direction: "lambda" (default) or "delta" |

`strong` |
whether use strong screening or not |

standardized beta

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