MDmiss: Mahalanobis distance (MD) for data with missing values In modi: Multivariate Outlier Detection and Imputation for Incomplete Survey Data

Description

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.

Usage

 `1` ```MDmiss(data, center, cov) ```

Arguments

 `data` the data as a dataframe or matrix. `center` the center to be used (may not contain missing values). `cov` the covariance to be used (may not contain missing values).

Details

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.

Value

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

Beat Hulliger

References

Béguin, C., and Hulliger, B. (2004). Multivariate outlier detection in incomplete survey data: The epidemic algorithm and transformed rank correlations. Journal of the Royal Statistical Society, A167 (Part 2.), pp. 275-294.

mahalanobis

Examples

 ```1 2``` ```data(bushfirem, bushfire) MDmiss(bushfirem, apply(bushfire, 2, mean), var(bushfire)) ```

Example output

```         1          2          3          4          5          6          7
7.2160085  4.3257008  0.8440923  1.5134291  2.0969730  7.7609395 16.0537514
8          9         10         11         12         13         14
12.7285244 13.9153844  5.4796427  6.1669445  8.2130006  8.9678140  1.2510538
15         16         17         18         19         20         21
6.5831730  2.8194816  2.3046020  5.2032014  2.7992887  2.3844491  2.1648484
22         23         24         25         26         27         28
3.6412421  1.0753593  1.8880181  1.1136020  0.8451837  1.5872090  2.4596324
29         30         31         32         33         34         35
5.6991877  4.5959379  5.7128476  8.3101486  5.3993714  4.6988444  5.0190419
36         37         38
6.4838249  4.8498564  7.2191933
```

modi documentation built on May 2, 2019, 6:38 a.m.