entropy {bigdatadist} | R Documentation |

## Entropy Computation

### Description

This function allows you to compute the family of alpha entropy as stated in Martos et al (2018).

### Usage

`entropy(X,alpha=2,k.neighbor,scale=FALSE) `

### Arguments

`X` |
data in a matrix where variables are in columns and observations are in rows. |

`alpha` |
a parameter defining the entropy function. |

`k.neighbor` |
number of neighbour points to consider in the computation of entropy. |

`scale` |
logical variable indicating if scaling is required. |

### Details

The function computes the alpha entropy and the local alpha entropy (see reference for further details) of a data set using a non parametric density estimator.

### Value

`local.entropy` |
local entropy relative to each point in the sample. |

`entropy` |
estimated entropy. |

### References

Martos, G. et al (2018): Entropy Measures for Stochastic Processes with Applications in Functional Anomaly Detection. Entropy 20(1): 33 (2018).

### Examples

```
require(MASS);
data = mvrnorm(100,c(0,0),diag(2));
entropy(data, alpha = 2, k.neighbor = 10, scale = FALSE)
```

[Package

*bigdatadist*version 1.1 Index]