Performs maximum likelihood estimation of the population size, degree distribution and theta [explain] allowing (a) "soft" constraints on theta and (b) an input Sij matrix.

1 2 3 | ```
estimate.rds3(data, Sij, init, const, arc = FALSE,
maxit = 10000, initial.thetas, theta.minimum,
theta.range)
``` |

`data` |
An integer vector of the degrees of each individual sampled. |

`Sij` |
An integer matrix of the counts of individuals with rank j at sampling period t. Row names correspond to the degrees. |

`init` |
Optional initialization values. |

`const` |
Control the concentration of the mapping of the theta parameter from the contstrained domain to the real line. |

`arc` |
Should the degrees in the snowball be taken in account (TRUE) or just the size of the snowball (FALSE). Defaults to FALSE. |

`maxit` |
Number of maximal optimization iterations. |

`initial.thetas` |
Vector of initial values of theta parameter. |

`theta.minimum` |
Lower bound on the allowed values of theta. |

`theta.range` |
Allowed range of theta values. From theta.minimum to theta.minimum+range. |

Jonathan Rosenblatt

1 2 3 |

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