This function is used to estimate the likelihood based on a set of parameters.

1 2 3 |

`data` |
Dataset generated with add_format |

`parametersfit` |
Set of parameters to be fitted |

`parametersfixed` |
Set of fixed parameters |

`zero_counts` |
example c(TRUE, TRUE, FALSE) indicates whether the zeros have been recorder for each of these timeseries. Defaut is TRUE for all. |

`method_incertitude` |
2 [default] is the correct one from a statistical point of view; |

`result` |
An object obtained after fit_phenology() |

`infinite` |
Number of iterations for dSnbinom() used for method_incertitude='sum' |

`zero` |
If the theoretical nest number is under this value, this value wll be used |

likelihood_phenology estimate likelihood for a set of parameters.

The likelihood of the data with the parameters

Marc Girondot

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | ```
## Not run:
# Read a file with data
Gratiot<-read.delim("http://max2.ese.u-psud.fr/epc/conservation/BI/Complete.txt", header=FALSE)
data(Gratiot)
# Generate a formated list nammed data_Gratiot
data_Gratiot<-add_phenology(Gratiot, name="Complete",
reference=as.Date("2001-01-01"), format="%d/%m/%Y")
# Generate initial points for the optimisation
parg<-par_init(data_Gratiot, parametersfixed=NULL)
# Estimate likelihood with this initial set of parameters
likelihood_phenology(data=data_Gratiot, parametersfit=parg, parametersfixed=NULL)
# Or directly from a result object
likelihood_phenology(result=result_Gratiot)
## End(Not run)
``` |

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