post_loss: function to calculate posterior predictive loss given the...
In hierarchicalDS: Functions to Perform Hierarchical Analysis of Distance Sampling Data
Description
Usage
Arguments
Value
Author(s)
Description
function to calculate posterior predictive loss given the output object from hierarchicalDS
Usage
1
post_loss(Out, burnin = 0)
Arguments
Out
Output object from running hierarchicalDS
burnin
Any additional #'s of values from beginning of chain to discard before calculating PPL statistic (default is 0)
Value
A matrix with posterior variance (P), sums of squares (G) for the posterior mean and median predictions (compared to Observations), and total posterior loss (D)
Author(s)
Paul B. Conn
hierarchicalDS documentation built on July 3, 2019, 1:07 a.m.
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Description Usage Arguments Value Author(s)
Description
function to calculate posterior predictive loss given the output object from hierarchicalDS
Usage
1 | post_loss(Out, burnin = 0)
|
Arguments
Out |
Output object from running hierarchicalDS |
burnin |
Any additional #'s of values from beginning of chain to discard before calculating PPL statistic (default is 0) |
Value
A matrix with posterior variance (P), sums of squares (G) for the posterior mean and median predictions (compared to Observations), and total posterior loss (D)
Author(s)
Paul B. Conn
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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