For each observation the missing dimensions are omitted before calculating the MD. The MD contains a correction factor *p/q* to account for the number of observed values, where *p* is the number of variables and *q* is the number of observed dimensions for the particular observation.

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`data` |
The data as a data frame or matrix. |

`center` |
The center to be used (may not contain missing values). |

`cov` |
The covariance to be used (may not contain missing values). |

The function loops over the observations. This is not optimal if only a few missingness patterns occur. If no missing values occur the function returns the Mahalanobis distance.

The function returns a vector of the (squared) Mahalanobis distances.

Beat Hulliger

B\'eguin, C., and Hulliger, B. (2004). Multivariate oulier detection in incomplete survey data: The epidemic algorithm and transformed rank correlations. Journal of the Royal Statistical Society, A 167(Part 2.), 275-294.

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