Description Usage Arguments Value Author(s)

This returns the first derivative of the posterior density of a spatial GEV model with respect to a random effect on the precision parameter. It is used in forming the Metropolis-Hastings update of this parameter.

1 | ```
g.prime(tau, tau.hat, varsigma, xi, kappa.hat, eps)
``` |

`tau` |
Current value of the random effect |

`tau.hat` |
The conditional mean of the random effect given the others and the current Gaussian process parameters. |

`varsigma` |
The conditional variance of the random effect based on the Gaussian process parameters |

`xi` |
The current shape parameter for this location |

`kappa.hat` |
The linear part of the precision parameters |

`eps` |
The vector of residuals based on the observations at this site and the associated location parmeter |

A scalar giving the first derivative, which is used to form the Metropolis-Hasting update.

Alex Lenkoski <[email protected]>

spatial.gev.bma documentation built on May 29, 2017, 9:10 a.m.

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