Description Usage Arguments Value References Examples

View source: R/population.test.MinPv.R

Identify the nonzero partial correlations in one-sample population,
based on controlling the exceedance rate of the false discovery proportion (FDP)
at *α=0.05*. The method is based on the minimum of the p-values.
Input data *Z* , contains values of p interested variables.

1 | ```
population.test.MinPv(popEst, alpha = 0.05, c0 = 0.1)
``` |

`popEst` |
A |

`alpha` |
significance level, default value is |

`c0` |
threshold of the exceedance rate of the false discovery proportion (FDP),
default value is |

A *p*p* matrix with values 0 or 1.

Genovese C., and Wasserman L. (2006).
Exceedance Control of the False Discovery Proportion,
*Journal of the American Statistical Association*, 101, 1408-1417

Qiu Y. and Zhou X. (2021).
Inference on multi-level partial correlations
based on multi-subject time series data,
*Journal of the American Statistical Association*, 00, 1-15

1 2 3 4 | ```
## Quick example for the one-sample population inference
data(popsimA)
pc = population.est(popsimA) # estimating partial correlation coefficients
Res = population.test.MinPv(pc) # conducting hypothesis test
``` |

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