This function tries to optimally split a given subpopulation into two smaller subpopulations.

1 2 | ```
splitConnMat(indices, conn.mat, beta, tries = 5, threshold = 1e-10,
alpha = 0.1, maxit = 500)
``` |

`indices` |
vector of indices of sites in a subpopulation |

`conn.mat` |
a square connectivity matrix. This matrix has typically been normalized and made symmetric prior to using this function. |

`beta` |
controls degree of splitting of connectivity matrix, with larger values generating more subpopulations. |

`tries` |
how many times to restart the optimization algorithm. Defaults to 5. |

`threshold` |
controls when to stop each "try". Defaults to 1e-10. |

`alpha` |
controls rate of convergence to solution |

`maxit` |
Maximum number of iterations to perform per "try". |

List with one or two elements, each containing a vector of indices of sites in a subpopulations

David M. Kaplan dmkaplan2000@gmail.com

Jacobi, M. N., Andre, C., Doos, K., and Jonsson, P. R. 2012. Identification of subpopulations from connectivity matrices. Ecography, 35: 1004-1016.

See also `optimalSplitConnMat`

,
`recSplitConnMat`

,
`subpopsVectorToList`

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