cor.by.class {CCM} | R Documentation |

## Finds within class correlations

### Description

Finds within class correlations between samples of each class type, which is useful for identifying extreme observations and assessing whether CCM is appropriate for classification.

### Usage

```
cor.by.class(x, y, method = "pearson", use = "complete")
```

### Arguments

`x` |
data matrix with variables in rows and samples in columns |

`y` |
classes corresponding to the columns of |

`method` |
the type of correlation to use, either 'pearson' (the default) or 'spearman' |

`use` |
instructions for handling missing values. See details and |

### Details

Calculates correlations between each pair of observations within each class. The correlation between an observation and itself is ignored.

The default correlation is the Pearson product moment correlation. If `method`

is 'spearman', then the Spearman's rank correlation is used, which is the Pearson correlation calculated using the ranks of the data.

Correlations are calculated class-wise on the matrix of observations of each class separately. Therefore, missing values may be handled differently for different classes.

### Value

A list with each element a vector of correlations between samples of a different class.

### Author(s)

Garrett M. Dancik and Yuanbin Ru

### Examples

```
data(data.expr)
data(data.gender)
K = cor.by.class(data.expr, data.gender)
## visualize the results ##
boxplot(K, xlab = "gender")
```

*CCM*version 1.2 Index]