This function calculates the Bimodality Coefficient of a data vector with the option for a finite sample (bias) correction. This bias correction is important to correct for the (well-documented) finite sample bias. The bimodality coefficient has a range of zero to one (that is: [0,1]) where a value greater than "5/9" suggests bimodality. The maximum value of one ("1") can only be reached when the distribution is composed of two point masses.

1 | ```
bimodality_coefficient(x, finite = TRUE, ...)
``` |

`x` |
Data vector. |

`finite` |
Should the finite sample size correction be applied to the skewness and kurtosis measures? Defaults to TRUE. |

`...` |
Pass through arguments. |

Ellison, A. (1987). Effect of Seed Dimorphism on the Density-Dependent Dynamics of Experimental Populations of Atriplex triangularis (Chenopodiaceae). American Journal of Botany, 74(8), 1280-1288.

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