backShift |
Estimate connectivity matrix of a directed graph with linear effects and hidden variables. |

bootstrapBackShift |
Computes a simple model-based bootstrap confidence interval for success of joint diagonalization procedure. The model-based bootstrap approach assumes normally distributed error terms; the parameters of the noise distribution are estimated with maximum likelihood. |

computeDiagonalization |
Computes the matrix Delta Sigma_{c,j} resulting from the joint diagonalization for a given environment (cf. Eq.(7) in the paper). If the joint diagonalization was successful the matrix should be diagonal for all environments $j$. |

exampleAdjacencyMatrix |
Example adjacency matrix |

generateA |
Generates a connectivity matrix A. |

metricsThreshold |
Performance metrics for estimate of connectiviy matrix A. |

plotDiagonalization |
Plots the joint diagonalization. I.e. if it was successful the matrices should all be diagonal. |

plotGraphEdgeAttr |
Plotting function to visualize directed graphs |

plotInterventionVars |
Plots the estimated intervention variances. |

simulateInterventions |
Simulate data of a causal cyclic model under shift interventions. |