nn.ent {abctools} | R Documentation |

## Works out entropy of a sample.

### Description

The function computes the k nearest neighbour sample entropy.

### Usage

```
nn.ent(th, k=4)
```

### Arguments

`th` |
The sample from which to compute the entropy. |

`k` |
The order (number of neighbours) of the sample entropy calculation. |

### Details

The sample entropy gives a measure of information in a (posterior) sample, or lack of it.

### Value

The k nearest neighbour entropy from the sample.

### Warning

For high-dimensional posterior samples, the `nn.ent`

calculation is quite computationally intensive.

### Author(s)

Matt Nunes

### References

Nunes, M. A. and Prangle, D. (2016) abctools: an R package for tuning
approximate Bayesian computation analyses. *The R Journal*
**7**, Issue 2, 189–205.

Singh, H. et al. (2003) Nearest neighbor estimates of entropy. *Am. J. Math. Man. Sci.*,**23**, 301–321.

Shannon, C. E. and Weaver, W. (1948) A mathematical theory of communication. *Bell Syst. Tech. J.*, **27**, 379–423.

### See Also

### Examples

```
# create a dummy sample to calculate an entropy measure:
theta<-rnorm(10000)
nn.ent(theta)
```

*abctools*version 1.1.7 Index]