Description Usage Arguments Details Value Author(s) References

Testing the equality of high dimensional mean vector to zero using the method developed in arXiv:1406.1939 [math.ST]

1 |

`X` |
The |

`m` |
The number of Monte-Carlo samples in the test, default to be |

`filter` |
A logical indicator of the filtering process, defaul to be TRUE |

`S` |
Covariance matrix of |

`alpha` |
The significant level of the test. |

`DNAME` |
Defaul input. |

Implement the method developed in arXiv:1406.1939 [math.ST] to test whether a high dimensional mean vector is zero or not, which is equivalent
to test *H_0: μ=μ_0* for some prescribed value *μ_0* which can be subtracted from the data. The procedure utilizes bootstrap concept and derive the critical values using
independent Gaussian vectors whose covariance is estimated using sample covariance matrix.

Value of testing statistics, p-values (the non-studentized statistic and the studentized statistic respectively), alternative hypothesis, and the name of testing procedure.

Tong He

J. Chang, W. Zhou and W.-X. Zhou, Simulation-Based Hypothesis Testing of High Dimensional Means Under Covariance Heterogeneity (2014), arXiv:1406.1939.

HDtest documentation built on Sept. 22, 2018, 1:05 a.m.

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