Safe Haskell | None |
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# Documentation

Techniques used to smooth the nearest values when calculating quantile functions. R2 is used by default, and the numbering convention follows the use in the R programming language, as far as it goes.

R1 | Inverse of the empirical distribution function |

R2 | .. with averaging at discontinuities (default) |

R3 | The observation numbered closest to Np. NB: does not yield a proper median |

R4 | Linear interpolation of the empirical distribution function. NB: does not yield a proper median. |

R5 | .. with knots midway through the steps as used in hydrology. This is the simplest continuous estimator that yields a correct median |

R6 | Linear interpolation of the expectations of the order statistics for the uniform distribution on [0,1] |

R7 | Linear interpolation of the modes for the order statistics for the uniform distribution on [0,1] |

R8 | Linear interpolation of the approximate medans for order statistics. |

R9 | The resulting quantile estimates are approximately unbiased for the expected order statistics if x is normally distributed. |

R10 | When rounding h, this yields the order statistic with the least expected square deviation relative to p. |

HD | The Harrell-Davis quantile estimator based on bootstrapped order statistics |

estimateBy :: Fractional r => Estimator -> Rational -> Int -> Estimate rSource