Description Usage Arguments Value References Examples

View source: R/CorShrinkData.R

Performs adaptive shrinkage of the sample correlations starting from a data matrix (possibly containing NAs).

1 2 3 4 5 |

`data` |
The samples by features data matrix. May contain NA values. |

`sd_boot` |
A Boolean variable indicating if the standard errors of the Fisher z-scores should be computed via Bootstrap methods or through asymptotic formulation of the problem. |

`type` |
character. Either "cor" or "pcor" - depending on whether to use correlation or partial correlation. Default is "cor". |

`cor_method` |
The method of correlation used. May be "pearson", "spearman" or "kendall" depending on the type of correlation to be used by the user. |

`thresh_up` |
Upper threshold for correlations. Defaults to 0.99 |

`thresh_down` |
Lower threshold for correlations. Defaults to -0.99. |

`image` |
character. options for plotting the original or the corshrink matrix.
If |

`tol` |
The tolerance chosen to check how far apart the CorShrink matrix is from the nearest positive definite matrix before applying PD completion. |

`nboot` |
The number of bootstrap samples if |

`image.control` |
Control parameters for the image when |

`report_model` |
if TRUE, outputs the full adaptive shrinkage output, else outputs the shrunken vector. Defaults to FALSE. |

`maxiter` |
The maximum number of iterations run for the adaptive shrinkage EM algorithm. Default is 1000. |

`ash.control` |
The control parameters for adaptive shrinkage |

Returns an adaptively shrunk version of the sample correlations matrix.

False Discovery Rates: A New Deal. Matthew Stephens bioRxiv 038216; doi: http://dx.doi.org/10.1101/038216

1 2 | ```
data("sample_by_feature_data")
out <- CorShrinkData(sample_by_feature_data, image = "both")
``` |

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