Outputs Effective Sample Size Diagonis for MCMC run

Execute one Gibbs step on a cycle keeping row and column sums fixed

1 | ```
ERE_step_cycle(r, c, L, lambda, p, eps = 1e-10)
``` |

`r` |
Row indies of cycle, starting at 0 (vector of length k) |

`c` |
Column indices of cycle, starting at 0 (vector of length k) |

`L` |
nxn matrix with nonnegative values (will be modified) |

`lambda` |
nxn matrix of intensities |

`p` |
nxn matrix of probabilities (must be in [0,1] and 0 on diagonal) |

`eps` |
Threshold for values to be interpreted as equal to 0 (default = 1e-10) |

no return value

1 2 3 4 5 6 |

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