calc_eval_measures: Functions to calculate information divergence measures for...
In cbrown5/remixsiar: Post-processing of stable isotope mixing models
Description
Usage
Arguments
Details
Value
Author(s)
Description
Functions to calculate information divergence measures for mixsiar models
Usage
1
2
calcinfo_mixsiar(mixmodlist, prior.control = NULL, metric = c("hellinger",
"kldivergence"))
Arguments
mixmodlist
a list with a simmr_input and simmr_output object.
dp
the prior used, generated with function default_prior
, if NULL, assumes the default.
Details
take an object from simmr_fitsims and calculates and
returns evaluation metrics.
Value
Relevant information or evaluation measure,
assuming default priors for simmr.
Author(s)
Christopher J. Brown
cbrown5/remixsiar documentation built on April 26, 2020, 12:40 a.m.
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Description Usage Arguments Details Value Author(s)
Description
Functions to calculate information divergence measures for mixsiar models
Usage
1 2 | calcinfo_mixsiar(mixmodlist, prior.control = NULL, metric = c("hellinger",
"kldivergence"))
|
Arguments
mixmodlist |
a |
dp |
the prior used, generated with function default_prior , if NULL, assumes the default. |
Details
take an object from simmr_fitsims and calculates and
returns evaluation metrics.
Value
Relevant information or evaluation measure, assuming default priors for simmr.
Author(s)
Christopher J. Brown
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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