This function measures the Amari error between two matrices.

1 | ```
amari_distance(Q1, Q2)
``` |

`Q1` |
First matrix. |

`Q2` |
Second matrix. |

The Amari error *D(Q1|Q2)* between two M x M matrices *Q1* and *Q2* is evaluated through

*D(Q1|Q2)=\frac{1}{2M(M-1)}∑_{j=1}^M≤ft(\frac{∑_{i}|a_{ij}|}{max_{i}|a_{ij}|}-1\right)+\frac{1}{2M(M-1)}∑_{i=1}^M≤ft(\frac{∑_{j}|a_{ij}|}{max_{j}|a_{ij}|}-1\right),*

where *Q2* is invertible and *a_{ij}* is the *ij*th element of *Q1Q2^{-1}*.

It returns the Amari error between two matrices *Q1* and *Q2*.

Lee, S., Shen, H., Truong, Y. and Zanini, P.

Amari, S., Cichocki, A., Yang, H. et al. (1996). A New Learning Algorithm for Blind Signal Separation. *Advances in Neural Information Processing Systems*, **8**, 757–763

Bach, F., Jordan, M. (2003). Kernel Independent Component Analysis. *Journal of Machine Learning Research*, **3**, 1–48

1 2 3 4 5 | ```
M <- 4
A <- matrix(rnorm(M*M),M,M)
B <- matrix(rnorm(M*M),M,M)
amari_distance(A,B)
``` |

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.