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BayHaz (version 0.1-3)

CPPpriorElicit: Function to Set Hyperparameters of CPP Priors

Description

A function to set the hyperparameters of a CPP prior distribution, following the procedure described in La Rocca (2005).

Usage

CPPpriorElicit(r0 = 1, H = 1, T00 = 1, M00 = 1, extra = 0)

Arguments

r0
prior mean hazard rate ($r_0$)
H
corresponding coefficient of variation
T00
time-horizon of interest ($T_\infty$)
M00
number of extremes within the time-horizon in a "typical" hazard rate trajectory ($M_\infty$)
extra
number of additional CPP jumps (compared with default)

Value

  • A list with nine components:
  • r0prior mean hazard rate (copy of the input argument)
  • Hcorresponding coefficient of variation (copy of the input argument)
  • T00time-horizon of interest (copy of the input argument)
  • M00number of extremes within the time-horizon in a "typical" hazard rate trajectory (copy of the input argument)
  • ashape parameter of the jump-size distribution (always equal to 1)
  • sdstandard deviation of the Gaussian kernel (bandwidth)
  • qexpected number of CPP jumps per time unit
  • brate parameter of the jump-size distribution
  • Fmaximum number of jumps within the time-horizon (with high probability)

Details

A CPP prior hazard rate is defined, for $0
  • $\sigma_j$is the time of the$j$-th jump of a CPP process with gamma distributed jump-sizes
  • $\xi_j$is the$j$-th jump-size of the above process
  • $k$is a zero-mean Gaussian density (kernel)
  • $F$is a positive integer such that (with high probability)$\sigma_{F+1}$is much larger than$T_\infty$
  • $\xi_0$is an independent random variable with the same distribution as$\xi_j$
  • $k_0$is a suitable function such that the mean of$rho(t)$does not depend on$t$
  • The elicitation procedure makes the mean of $rho(t)$ identically equal to $r_0$ and its standard deviation approximately equal to $Hr_0$. An exponential distribution is selected for the jump-sizes. The kernel bandwidth choice is based on $M_\infty$ (and $T_\infty$).

    References

    Luca La Rocca (2005). On Bayesian Nonparametric Estimation of Smooth Hazard Rates with a View to Seismic Hazard Assessment. Research Report n. 38-05, Department of Social, Cognitive and Quantitative Sciences, Reggio Emilia, Italy.

    See Also

    BayHaz-package, CPPpriorSample, CPPpostSample

    Examples

    Run this code
    # ten events per century with unit coefficient of variation
    # fifty year time horizon with a couple of extremes in a "typical" trajectory
    hypars<-CPPpriorElicit(r0 = 0.1, H = 1, T00 = 50, M00 = 2)

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