waic.tridim_transformation: Computes widely applicable information criterion (WAIC).
In TriDimRegression: Bayesian Statistics for 2D/3D Transformations
Description
Usage
Arguments
Value
Examples
Description
Computes widely applicable information criterion
via loo library. It can be used for a model comparison via
loo::loo_compare() function.
Usage
1
2
## S3 method for class 'tridim_transformation'
waic(x, ...)
Arguments
x
A [tridim_transformation[tridim_transformation-class() object
...
unused
Value
A named list, see loo::waic() for details.
Examples
1
2
3
4
5
euc2 <- fit_transformation(depV1+depV2~indepV1+indepV2,
NakayaData, transformation = 'euclidean')
aff2 <- fit_transformation(depV1+depV2~indepV1+indepV2,
NakayaData, transformation = 'affine')
loo::loo_compare(waic(euc2), waic(aff2))
TriDimRegression documentation built on May 4, 2021, 9:08 a.m.
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Description Usage Arguments Value Examples
Description
Computes widely applicable information criterion via loo library. It can be used for a model comparison via loo::loo_compare() function.
Usage
1 2 | ## S3 method for class 'tridim_transformation'
waic(x, ...)
|
Arguments
x |
A [tridim_transformation[ |
... |
unused |
Value
A named list, see loo::waic() for details.
Examples
1 2 3 4 5 | euc2 <- fit_transformation(depV1+depV2~indepV1+indepV2,
NakayaData, transformation = 'euclidean')
aff2 <- fit_transformation(depV1+depV2~indepV1+indepV2,
NakayaData, transformation = 'affine')
loo::loo_compare(waic(euc2), waic(aff2))
|
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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