Description Usage Arguments Value

Fitting a parametric multivariate mixed-Poisson model via a Gaussian copula with a log-normal marginal distribution of random effects

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`formula` |
a formula object with an obect of the type |

`data` |
a 'data.frame' which has variables in 'formula' |

`frailty` |
a charhacter string specifying a group |

`dist` |
a vector of character strings specifying a distribution for the baseline for each type of events. If it is a character string, it applies to all types of events. Default is "weibull". Other options are "ev", "loglogistic", and "lognormal". See |

`ntype` |
the number of types of events. |

`model` |
logical value: if |

`model.matrix` |
logical value: if |

`control` |
an object of class specifying control options created by |

`init` |
a list specifying inital values of a vector of variances of random effects and dependence parameters. Default initial value for a variance of random effect is 1 and 0 for the dependence parameter. |

`eventnames` |
a vector of character string speficying event names |

`parallel` |
logical value: if |

`ncore` |
the number of cores if |

an object of class `parmfrailty`

representing the fit.

`beta.coefficients` |
a list of each types of events of the estimated regressoin coefficients. |

`logalpha.coefficients` |
a list of each types of events of the estimated log of baseline parameters. |

`sig2` |
a vector of the estimated variances of random effects. |

`rho` |
a vector of the estimated dependence parameters from a Gaussian copula function. |

`ktau` |
a vector of the estimated Kendall's tau from a Gaussian copula function. |

`logLik` |
a value of log likelihood at the final values of the parameters. |

`iter` |
the number of iterations used. |

`conv` |
an integer code for the convergence. See |

`var` |
a variance-covariance matrix of the estimates. |

`betavar` |
a list of each type of variances of the regression coefficient estimates. |

`logalphavar` |
a list of each type of variances of the log of baseline parameter estimates. |

`thetavar` |
a list of each type of variacnes of the regression coefficients and the log of baseline parameter estimates. |

`sig2var` |
a vector of the variances of random effects variances estimates. |

`rhovar` |
a vector of the dependence parameter estimates. |

`varnames` |
a list of event names and variable names. |

`control` |
a list of control arguments used. |

`n` |
the number of sample size. |

`nevent` |
a vector of the number of each types of events. |

`neventtype` |
the number of types of events. |

`nknot` |
the number nodes used in Gaussian-quadrature. |

`margins` |
a vector of character strings specyting marginal distributions of random effects. |

The object will also contain the following: dist, copula, model, call, optionally x, and model.

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