Description Usage Arguments Details Value Note Author(s) References See Also Examples

The function "DNetNPN" tests for the structural difference between two nonparanormal graphical models with false discovery rate control.

1 | ```
DNetNPN(Data_mat1,Data_mat2,Beta_mat1,Beta_mat2,alpha)
``` |

`Data_mat1` |
An n1 by p data matrix for the first NPNGM, where each row represents one observation |

`Data_mat2` |
An n2 by p data matrix for the second NPNGM, where each row represents one observation |

`Beta_mat1` |
A p-1 by p coefficient matrix for the first NPNGM, where each column contains the regression coefficients of one variable on the other p-1 variables. |

`Beta_mat2` |
A p-1 by p coefficient matrix for the second NPNGM. See |

`alpha` |
User-specified FDR level |

The multiple testing procedure asymptotically controls the false discovery rate. See Zhang (2017) for details.

Estimated differential network, where "1" represents a differential edge and "0" represents a common edge (or no edge) between two NPNGMs.

Besides lasso, other estimators such as Dantzig selector or square-root lasso can also be used. See detailed discussion in Liu (2017) and Zhang (2017).

Qingyang Zhang

Li, X., Zhao, T., Yuan, X., Liu, H. (2015). The flare Package for High Dimensional Linear Regression and Precision Matrix Estimation in R. Journal of Machine Learning Research, 16:553-557

Liu, H., Lafferty, J., Wasserman, L. (2009). The Nonparanormal: Semiparametric Estimation of High Dimensional Undirected Graphs. Journal of Machine Learning Research, 10:2295-2328

Liu, W. (2017). Structural Similarity and Difference Testing on Multiple Sparse Gaussian Graphical Models. Annals of Statistics, 45(6):2680-2707

Tibshirani, R. (1996). Regression Shrinkage and Selection via the Lasso. Journal of the Royal Statistical Society Series B, 58(1):267-288

Zhang, Q. (2017). Structural Difference Testing on Multiple Nonparanormal Graphical Models with False Discovery Rate Control. Preprint.

DNetGGM()

1 2 3 4 5 | ```
Data1=read.table(system.file("extdata","Data1.txt",package="DNetFinder"),header=FALSE)
Data2=read.table(system.file("extdata","Data2.txt",package="DNetFinder"),header=FALSE)
BetaNPN1=read.table(system.file("extdata","BetaNPN1.txt",package="DNetFinder"),header=FALSE)
BetaNPN2=read.table(system.file("extdata","BetaNPN2.txt",package="DNetFinder"),header=FALSE)
est_DNNPN=DNetNPN(Data1,Data2,BetaNPN1,BetaNPN2,alpha=0.1)
``` |

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