waic_all: Compute WAIC for all outcomes.
In ktw5691/psychtm: Text Mining Methods for Psychological Research
Description
Usage
Arguments
Value
Examples
Description
Compute WAIC for all outcomes.
Usage
1
waic_all(iter, l_pred)
Arguments
iter
The length of the sampled chain.
l_pred
A iter x D matrix of predictive likelihoods (NOT log-likelihoods).
Value
Vector of (1) WAIC for model, (2) standard error for WAIC, and (3)
the effective number of parameters.
Examples
1
2
3
data(teacher_rate)
fit_mlr <- gibbs_mlr(rating ~ grade, data = teacher_rate, m = 5)
waic_all(iter = 5, t(lpd(fit_mlr)))
ktw5691/psychtm documentation built on Nov. 3, 2021, 9:10 a.m.
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Description Usage Arguments Value Examples
Description
Compute WAIC for all outcomes.
Usage
1 | waic_all(iter, l_pred)
|
Arguments
iter |
The length of the sampled chain. |
l_pred |
A |
Value
Vector of (1) WAIC for model, (2) standard error for WAIC, and (3) the effective number of parameters.
Examples
1 2 3 | data(teacher_rate)
fit_mlr <- gibbs_mlr(rating ~ grade, data = teacher_rate, m = 5)
waic_all(iter = 5, t(lpd(fit_mlr)))
|
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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