
Interpret WAIC value - Cross Validated
2020年7月11日 · The value by itself isn’t interpretable. It could be close to zero, greater than a million, or even negative. It is only useful for comparing models. Note that your models must be fit to the same data though in order to compare WAIC values.
Can WAIC be used to compare Bayesian linear regression models …
2018年1月25日 · Since you ask about WAIC, it helps if we forget deviance and focus on (negative) log score as in WAIC paper. First to make the terms more clear, p(y|theta) as a function of y is an observation model and p(y|theta) as a function of theta is a likelihood.
How to calculate WAIC from a JAGS model, and fix p_waic issue?
I wanted to calculate WAIC as I have heard it is more robust for hierarchical models. Below is a simplified version of my JAGS code, I have 3 continuous response variables, Dim.1, Dim.2 and Dim.3, and use partial pooling to allow the coefficients to vary …
regression - WAIC and model selection - Cross Validated
WAIC LOO 1 8408,2 8408,7 2 8408,8 8409,5 3 8407,7 8408,1 4 8408,1 8408,7 5 8407,3 8407,7 6 8407,8 8408,2 7 8407,9 8408,6 I was wondering if there is a rule to determine if the differences are large enough. I haven't found anything online. Clearly this are not the only tools I'm using.
bayesian - Can you compare AIC to WAIC? - Cross Validated
2021年2月26日 · Yes there doesn't seem to be a lot of active comparison of AIC to WAIC, so I guess I will just need to quickly re-run all the GLM models using a Bayesian estimator. Not too much of a headache I guess. If you have any official sources or explanation as to why they cannot be compared, would be greatly appreciated. $\endgroup$ –
markov chain montecarlo - DIC, WAIC in JAGS - Cross Validated
2018年3月6日 · There is more than 1 definition of DIC and WAIC. Celeux et al. (2006) provide 8 variants of DIC; Gelman and Vehtari (2013) provide 2 definitions of WAIC.
How to compare WAIC value when they are negative?
2023年7月15日 · The Widely Applicable Information Criterion (WAIC, Watanabe, (2010) "Asymptotic equivalence of Bayes cross validation and widely applicable information criterion in singular learning theory". Journal of Machine Learning Research 11 , 3571–3594.), is a fully Bayesian approach for estimating the
AIC,BIC,CIC,DIC,EIC,FIC,GIC,HIC,IIC - Cross Validated
WAIC uses the whole posterior density more effectively than DIC does, so Gelman et al. prefer it although it can be a pain to calculate in some cases. Cross-validation does not rely on any particular formula, but it can be computationally prohibitive for many models.
WAIC for model comparisons--overly conservative?
2019年7月31日 · 1) WAIC is overly conservative, and I'm better off interpreting model posterior predictions . 2) Small effects are detectable in-model, but are unlikely to have an impact on predictive accuracy. 3) There is some characteristic of my simulated data/analyses (i.e., binomial outcome, priors) affecting the WAIC comparisons
bayesian - Testing difference between two models using WAIC …
2024年5月28日 · Two of the outputs from the bayesreg::bayesreg function are waic which is described in the help as "The Widely Applicable Information Criteria (WAIC) score for the model", and waic.dof which is described as "The effective degrees-of-freedom of …