computeDIC_ASV: Function for calculating DIC and Pb (Bayesian measures of...
In dsp: Dynamic Shrinkage Process and Change Point Detection
computeDIC_ASV R Documentation
Function for calculating DIC and Pb (Bayesian measures of model complexity and fit by Spiegelhalter et al. 2002)
Description
Function for calculating DIC and Pb (Bayesian measures of model complexity and fit by Spiegelhalter et al. 2002)
Usage
computeDIC_ASV(y, beta, post_sigma2, post_loglike)
Arguments
y
the T x 1 vector of time series observations.
beta
the known mean of the process. 0 by default.
post_sigma2
posterior samples of the variance, i.e. exp(h)
post_loglike
log likelihood based on the posterior sample.
Value
a list containing DIC and p_d. Two options for estimating both DIC and p_d, which are both included.
dsp documentation built on Aug. 21, 2025, 5:29 p.m.
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| computeDIC_ASV | R Documentation |
Function for calculating DIC and Pb (Bayesian measures of model complexity and fit by Spiegelhalter et al. 2002)
Description
Function for calculating DIC and Pb (Bayesian measures of model complexity and fit by Spiegelhalter et al. 2002)
Usage
computeDIC_ASV(y, beta, post_sigma2, post_loglike)
Arguments
y |
the |
beta |
the known mean of the process. 0 by default. |
post_sigma2 |
posterior samples of the variance, i.e. exp(h) |
post_loglike |
log likelihood based on the posterior sample. |
Value
a list containing DIC and p_d. Two options for estimating both DIC and p_d, which are both included.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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