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

View source: R/highD2popfunctions.R

Performs the generalized component test from Gregory et al. (2014) for the equality of two `p`

by `1`

population mean vectors given samples of sizes `n`

and `m`

when there are missing data.

1 | ```
GCT.test.missing(X, Y, r, smoother = "parzen", ntoorderminus = 2)
``` |

`X` |
the |

`Y` |
the |

`r` |
the lag window size for variance estimation. |

`smoother` |
the lag window used in the variance estimation. Possible values are |

`ntoorderminus` |
a value of |

`TSvalue` |
the unstudentized test statistic. |

`center` |
the centering constant for studentizing the test statistic. |

`var` |
the estimated variance of the unstudentized test statistic. |

`T` |
the studentized test statistic. |

`smoother` |
the choice of smoother used. |

`pvalue` |
the pvalue. |

`overallpctmiss` |
the overall proportion of values that are missing. |

`pctmissperX` |
a vector of length |

`pctmissperY` |
a vector of length |

Karl Gregory [email protected], http://www.stat.tamu.edu/~kbgregory.

Gregory, K., Carroll, R. J., Baladandayuthapani, V. and Lahiri, S. (2015). A two-sample test for equality of means in high dimension.
*Journal of the American Statistician*, to appear

1 2 3 4 5 6 | ```
data(chr1qseg)
X <- chr1qseg$X
Y <- chr1qseg$Y
GCT.test.missing(X,Y,r=20,smoother="parzen")
``` |

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