logp | R Documentation |
This function computes the negative log-posterior distribution of the Bayesian hierarchical model described in Myers et al (2011). It is a helper function and not meant to be used on its own.
logp(theta, deltaj, sigma2, i, k, eta, dat)
theta |
value of the error profile random effect at which the log.posterior distribution is calculated. |
deltaj |
vector of hospital random effect values. |
sigma2 |
scale parameter ( |
i |
error profile index for which the calculate of the log.posterior distribution is needed. |
k |
degrees of freedom ( |
eta |
skewness parameter ( |
dat |
an object of class "mederrData". |
For further details see Myers et al. (2011).
logp
returns a vector of log-posterior values.
Sergio Venturini sergio.venturini@unicatt.it,
Jessica A. Myers jmyers6@partners.org
Myers, J. A., Venturini, S., Dominici, F. and Morlock, L. (2011), "Random Effects Models for Identifying the Most Harmful Medication Errors in a Large, Voluntary Reporting Database". Technical Report.
bhm.constr.resamp
,
bhm.mcmc
,
bhm.resample
.
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