Description Usage Arguments Details Value Author(s) See Also Examples

Fit a set of OTU counts to the Poisson lognormal distribution.

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`n` |
vector of observed counts |

`start.mu` |
initial estimate for the lognormal mean |

`start.sig` |
initial estimate for the lognormal standard deviation |

`trunc` |
remove weight from zero counts? |

`method` |
optimization method for |

`control` |
list of parameters for |

`...` |
further parameters to go to |

The function estimates parameters mean `mu`

and standard deviation `sig`

.

The parameters must be given starting values for the optimization procedure. The default values here worked well when fitting OTUs in the referenced paper.

The function uses the optimization procedures in `optim`

to make the
maximum likelihood estimate. The `method`

and `control`

arguments are
passed to `optim`

.

A zero-truncated distribution (see `dpoilog`

) is assumed by default.
Truncation should only be turned off if all the known OTUs of the sequenced
community are known. In most cases, this is not applicable, since it is usually
not possible to know if an OTU had zero counts because it is not present in
the environment or if it is present but in low abundance.

`par` |
Maximum likelihood estimates of the parameters |

`p` |
Approximate fraction of OTUs revealed by the sample |

`logLval` |
Log likelihood of the data given the estimated parameters |

Scott Olesen swo@mit.edu

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