Calculate the bimodality coefficient for a numeric vector as specified in Pfister et al. (2013).

bimodality_coefficient(x, na.rm = FALSE)

x | a numeric vector. |
---|---|

na.rm | logical specifying whether missing values should be removed. |

A numeric value.

The calculation of the bimodality coefficient involves calculating the
skewness and kurtosis of the distribution first. For this, the
skew and kurtosi functions of the `psych`

package are used.
Note that type is set to "2" for these functions in accordance with
Pfister et al. (2013).

Pfister, R., Schwarz, K. A., Janczyk, M., Dale, R., & Freeman, J. B. (2013).
Good things peak in pairs: A note on the bimodality coefficient.
*Frontiers in Psychology, 4*, 700.
http://dx.doi.org/10.3389/fpsyg.2013.00700

skew and kurtosi for calculating skewness and kurtosis.

mt_check_bimodality for assessing bimodality using several methods in a mousetrap data object.

pfister_data_a <- rep(1:11, times=c(3,5,5,10,17,20,17,10,5,5,3)) bimodality_coefficient(pfister_data_a) #.34#> [1] 0.3360581pfister_data_b <- rep(1:11, times=c(2,26,14,6,2,0,2,6,14,26,2)) bimodality_coefficient(pfister_data_b) #.79#> [1] 0.7946887