# corDist: Correlation Distance Matrix Computation In MKmisc: Miscellaneous Functions from M. Kohl

## Description

The function computes and returns the correlation and absolute correlation distance matrix computed by using the specified distance measure to compute the distances between the rows of a data matrix.

## Usage

 ```1 2``` ```corDist(x, method = "pearson", diag = FALSE, upper = FALSE, abs = FALSE, use = "pairwise.complete.obs", ...) ```

## Arguments

 `x` a numeric matrix or data frame `method` the correlation distance measure to be used. This must be one of `"pearson"`, `"spearman"`, `"kandall"`, `"cosine"`, `"mcd"` or `"ogk"`, respectively. Any unambiguous substring can be given. `diag` logical value indicating whether the diagonal of the distance matrix should be printed by 'print.dist'. `upper` logical value indicating whether the upper triangle of the distance matrix should be printed by 'print.dist'. `abs` logical, compute absolute correlation distances `use` character, correponds to argument `use` of function `cor` `...` further arguments to functions `covMcd` or `covOGK`, respectively.

## Details

The function computes the Pearson, Spearman, Kendall or Cosine sample correlation and absolute correlation; confer Section 12.2.2 of Gentleman et al (2005). For more details about the arguments we refer to functions `dist` and `cor`. Moreover, the function computes the minimum covariance determinant or the orthogonalized Gnanadesikan-Kettenring estimator. For more details we refer to functions `covMcd` and `covOGK`, respectively.

## Value

`corDist` returns an object of class `"dist"`; cf. `dist`.

## Note

A first version of this function appeared in package SLmisc.

## Author(s)

Matthias Kohl Matthias.Kohl@stamats.de

## References

Gentleman R. Ding B., Dudoit S. and Ibrahim J. (2005). Distance Measures in DNA Microarray Data Analysis. In: Gentleman R., Carey V.J., Huber W., Irizarry R.A. and Dudoit S. (editors) Bioinformatics and Computational Biology Solutions Using R and Bioconductor. Springer.

P. J. Rousseeuw and A. M. Leroy (1987). Robust Regression and Outlier Detection. Wiley.

P. J. Rousseeuw and K. van Driessen (1999) A fast algorithm for the minimum covariance determinant estimator. Technometrics 41, 212-223.

Pison, G., Van Aelst, S., and Willems, G. (2002), Small Sample Corrections for LTS and MCD, Metrika, 55, 111-123.

Maronna, R.A. and Zamar, R.H. (2002). Robust estimates of location and dispersion of high-dimensional datasets; Technometrics 44(4), 307-317.

Gnanadesikan, R. and John R. Kettenring (1972). Robust estimates, residuals, and outlier detection with multiresponse data. Biometrics 28, 81-124.

## Examples

 ```1 2 3``` ```## only a dummy example M <- matrix(rnorm(1000), ncol = 20) D <- corDist(M) ```

### Example output

```
```

MKmisc documentation built on Aug. 8, 2021, 5:06 p.m.