Description Usage Arguments Value See Also

Takes pregenerated simulated GP models as input, and
models both the perturbation and additional perturbation variance as
GP models, that are all combined into a perturbed GP model. We sample
`reps`

data points from this at timepoints `obs`

1 2 3 4 | ```
simulategp.perturbed(N = 100, reps = 3, obs = c(0, 5, 10, 15, 20),
gps.ctrl = NULL, filename = NULL, xs = seq(0, 20, 0.2), l.noise = 12,
l.shape = 2, l.scale = 2.5, sigmaf.noise = 0.25, sigmaf.shape = 4,
sigmaf.scale = 0.5)
``` |

`N` |
number of gp's |

`reps` |
replicate observations |

`obs` |
observation timepoints |

`gps.ctrl` |
the GPS models to be perturbed |

`filename` |
file to save the results |

`xs` |
target timepoints |

`l.noise` |
Noise model lengthscale |

`l.shape` |
shape of lengthscale Gamma distribution |

`l.scale` |
scale of lengthscale Gamma distribution |

`sigmaf.noise` |
Noise model sigma.f |

`sigmaf.shape` |
shape of sigma.f Gamma distribution |

`sigmaf.scale` |
scale of sigma.f Gamma distribution |

List with

`simdata` |
Simulated datamatrix |

`gps` |
Simulated GPs |

nsgp documentation built on May 29, 2017, 11:47 p.m.

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