Interpolated quantile to quantile mapping between negative-binomial distributions with the same dispersion but different means. The Poisson distribution is a special case.

1 2 |

`x` |
numeric matrix of counts. |

`input.mean` |
numeric matrix of population means for |

`output.mean` |
numeric matrix of population means for the output values. If a vector, then of the same length as |

`dispersion` |
numeric scalar, vector or matrix giving negative binomial dispersion values. |

This function finds the quantile with the same left and right tail probabilities relative to the output mean as `x`

has relative to the input mean.
`q2qpois`

is equivalent to `q2qnbinom`

with `dispersion=0`

.

In principle, `q2qnbinom`

gives similar results to calling `pnbinom`

followed by `qnbinom`

as in the example below.
However this function avoids infinite values arising from rounding errors and does appropriate interpolation to return continuous values.

`q2qnbinom`

is called by `equalizeLibSizes`

to perform quantile-to-quantile normalization.

numeric matrix of same dimensions as `x`

, with `output.mean`

as the new nominal population mean.

Gordon Smyth

1 2 3 4 5 6 7 8 |

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.