residual_process | R Documentation |

Using random time change, this function compute the residual process, which is the inter-arrival time of a standard Poisson process. Therefore, the return values should follow the exponential distribution with rate 1, if model and rambda are correctly specified.

residual_process( component, inter_arrival, type, rambda_component, mu, beta, dimens = NULL, mark = NULL, N = NULL, Nc = NULL, lambda_component0 = NULL, N0 = NULL, ... )

`component` |
The component of type to get the residual process. |

`inter_arrival` |
Inter-arrival times of events. This includes inter-arrival for events that occur in all dimensions. Start with zero. |

`type` |
A vector of types distinguished by numbers, 1, 2, 3, and so on. Start with zero. |

`rambda_component` |
Right continuous version of lambda process. |

`mu` |
Numeric value or matrix or function. If numeric, automatically converted to matrix. |

`beta` |
Numeric value or matrix or function. If numeric, automatically converted to matrix, exponential decay. |

`dimens` |
Dimension of the model. If omitted, set to be the length of |

`mark` |
A vector of realized mark (jump) sizes. Start with zero. |

`N` |
A matrix of counting processes. |

`Nc` |
A matrix of counting processes weighted by mark. |

`lambda_component0` |
The initial values of lambda component. Must have the same dimensional matrix with |

`N0` |
The initial value of N |

`...` |
Further arguments passed to or from other methods. |

mu <- c(0.1, 0.1) alpha <- matrix(c(0.2, 0.1, 0.1, 0.2), nrow=2, byrow=TRUE) beta <- matrix(c(0.9, 0.9, 0.9, 0.9), nrow=2, byrow=TRUE) h <- new("hspec", mu=mu, alpha=alpha, beta=beta) res <- hsim(h, size=1000) rp <- residual_process(component = 1, res$inter_arrival, res$type, res$rambda_component, mu, beta)

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.