Model for Survival Analysis of Unbalanced Clusters using Archimedes Copula's (Note: you can also add other fields like references, authors,... See which ones are necessary)

1 2 3 |

`data` |
Input dataframe containing all variables. |

`time` |
Which variable name is the time covariate? |

`status` |
Which variable name is the status covariate? (more explanation?) |

`clusters` |
Which variable name is the cluster covariate? |

`covariates` |
Vector of 1 or more other covariates to be included in the model. If necessary a covariate should be a factor in the data frame. (NOTE: MULTIPLE COVARIATES NEED TO BE TESTED!!!) |

`stage` |
Can be 1 or 2 for 1 or 2 staged approached. See Details for more information. |

`copula` |
Which copula to user? Can either be |

`marginal` |
Which marginal to use? Can either be |

`n.piecewise` |
For |

`init.values` |
Initial values for parameters. This depends on the choice of the parameters |

`verbose` |
Print some in-between results as well as computation progress. |

`summary.print` |
Logical value to print a short summary at the end of the computation. |

WRITE DIFFERENT SECTIONS SECTION 1: Which marginals + copula's are available for stage 1 and 2 SECTION 2: Which parameters have to be given initially in all scenarios (stage 1 and 2) and in which order!! (note: the order will always be like this: lambdas, rho, theta, betas) SECTION 3: How are the initial parameters chosen if done automatically?

S3 List object

`Parameters` |
Data frame containing estimates and standard errors of parameters. |

`Kendall_Tau` |
Vector containing estimate and standard error of Kendall's Tau. |

`ParametersCov` |
If available, covariance matrix of the parameters. For 2-stage approaches this is only available for the Weibull marginal. |

`logllh` |
The log-likelihood value. |

`parameter.call` |
A list containing all arguments given to the function, as well as the initial parameter values and the elapsed time. |

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | ```
## Not run:
data("insem",package="Sunclarco")
result1 <- SunclarcoModel(data=insem,time="Time",status="Status",
clusters="Herd",covariates="Heifer",
stage=1,copula="Clayton",marginal="Weibull")
summary(result1)
result2 <- SunclarcoModel(data=insem,time="Time",status="Status",
clusters="Herd",covariates="Heifer",
stage=2,copula="Clayton",marginal="Cox",
verbose=TRUE)
summary(result2)
## ADD MORE EXAMPLES? => THESE EXAMPLES SHOULD BE USED IN VIGNETTE?
## End(Not run)
``` |

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