Adaptive LASSO and Network Regularized Generalized Linear Models

coef.cv_glmaag | Coefficients |

coef.glmaag | Coefficients for glmaag |

coef.ss_glmaag | Coefficients for ss_glmaag |

cv_glmaag | Cross validation for glmaag |

evaluate | Evaluate prediction |

evaluate_plot | Prediction visualization |

getcut | Get optimal cut points for binary or right censored phenotype |

getS | Estimate standardized Laplacian matrix |

glmaag | Fit glmaag model |

L0 | sample network 0 |

L1 | sample network 1 |

laps | Standardized Laplacian matrix |

plot.cv_glmaag | Cross validation plot |

plot.glmaag | Paths for glmaag object |

plot.ss_glmaag | Instability plot |

predict.cv_glmaag | Predict |

predict.glmaag | Prediction for glmaag |

predict.ss_glmaag | Prediction via stability selection |

print.cv_glmaag | the results of the cross validation model |

print.ss_glmaag | the results of the stability selection model |

runtheExample | Shiny app |

sampledata | Simulated data |

ss_glmaag | Stability selection for glmaag |

tune_network | tune two network |

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