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

The main function for All-Resolutions Inference (ARI) method based on critical vectors constructed
using the p-values permutation distribution. The function computes simultaneous lower bounds for the number of true discoveries
for each set of hypotheses specified in `ix`

controlling family-wise error rate.

1 2 3 |

`X` |
data matrix where rows represent the |

`ix` |
numeric vector which expresses the set of hypotheses of interest. It can be a vector with length equals |

`alpha` |
numeric value in '[0,1]'. It expresses the alpha level to control the family-wise error rate. |

`family` |
string character. Choose a family of confidence envelopes to compute the critical vector
from |

`delta` |
numeric value. It expresses the delta value, please see the references. Default to 0. |

`B` |
numeric value. Number of permutations, default to 1000. |

`pvalues` |
matrix of pvalues with dimensions |

`test.type` |
character string. Choose a type of tests among |

`complete` |
Boolean value. If |

`clusters` |
Boolean value. If |

`iterative` |
Boolean value. If |

`approx` |
Boolean value. Default @TRUE. If you are treating high dimensional data, we suggest to put |

`ncomb` |
Numeric value. If |

`step.down` |
Boolean value. Default @FALSE If you want to compute the lambda calibration parameter using the step-down approach put |

`max.step` |
Numeric value. Default to 10. Maximum number of steps for the step down approach, so useful when |

`...` |
Futher parameters. |

by default returns a list with the following objects: `discoveries`

: lower bound for the number of true discoveries in the set selected, `ix`

: selected variables. If `complete = TRUE`

the raw `pvalues`

and `cv`

critical vector are returned.

Angela Andreella

For the general framework of All-Resolutions Inference see:

Goeman, Jelle J., and Aldo Solari. "Multiple testing for exploratory research." Statistical Science 26.4 (2011): 584-597.

For permutation-based All-Resolutions Inference see:

Andreella, Angela, et al. "Permutation-based true discovery proportions for fMRI cluster analysis." arXiv preprint arXiv:2012.00368 (2020).

The type of tests implemented: `signTest`

`permTest`

.

1 2 3 | ```
datas <- simulateData(pi0 = 0.8, m = 1000, n = 30, power = 0.9, rho = 0,seed = 123)
out <- pARI(X = datas, ix = c(1:200),test.type = "one_sample")
out
``` |

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.