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Questions tagged [waic]

WAIC stands for the widely applicable information criterion (or Watanabe-Akaike information criterion). It is used for model selection, particularly in Bayesian settings. A smaller WAIC implies that a model should have lower predictive error.

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Comparing Bayesian hierarchical models with different sample sizes

I have observation data covering a certain period of time. I follow a block-maxima approach where the data are segmented into equal time intervals .My goal is to first develop a Bayesian Hierarchical ...
Ahmed Bayomi's user avatar
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How to compare WAIC value when they are negative?

How to compare WAIC values when they are negative? Is it still the lower the better? I got two complex Gaussian models with continuous probability density and the WAIC value are -8351 and -7321, ...
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Similarities between Bayes Factor and WAIC formulas?

It looks for me that WAIC and Bayes Factor are very similar in some circumstances. If we assume an equal prior for each parameter set Q (p(Q)), the Bayes Factor ...
adsurbum's user avatar
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When and how to use approximate leave-future-out cross-validation on hierarchical time series Stan model

I am fitting a hierarchical state space AR(1) model in Stan and am struggling use common model evaluation metrics on the model output. Computing the WAIC or using loo_cv in the loo package give ...
Alice's user avatar
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I'm doing model selection using DIC and WAIC. Can they be used to compare different models?

I'm comparing fitted models using the same dataset. The Models I am tweaking are Logit, Probit and a variation of Probit(Binary models). I can use DIC and WAIC to make these comparisons. Do you have a ...
Fabiano Rodrigues Coelho's user avatar
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Can you compare AIC to WAIC?

This may be a simple question, but I'm at a bit of a loss. Can I compare AIC to WAIC for the same model, one estimated using general linear models and one using Bayesian estimation? Or do I need to ...
bashity's user avatar
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Model comparison: WAIC value is large between nested random effect models

I have computed two models using INLA and following the proceedure laid out in this paper. As in the paper, the model has two random effects, one representing temporal relationships between data ...
SamPassmore's user avatar
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Interpret WAIC value

I am trying to figure out how to interpret the WAIC value computed based on two different Bayesian models. Is the value only used for comparing the models, such that the predictive capabilities of the ...
MarG's user avatar
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Variable selection with bayesian linear mixed models (the brms package)

I am fitting a bayesian linear mixed model in R with 6 variables and 2 random effects. Inclusion of all 6 variables is motivated by a well-founded hypothesis. Does it make sense to do variable ...
margie's user avatar
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3 votes
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WAIC for model comparisons--overly conservative?

I'm having a hard time wrapping my head around the relationship between model posterior predictions and model comparisons via WAIC. Specifically, how do I interpret findings where a model including ...
E.M.'s user avatar
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Bayes factors and predictive accuracy in model comparison in rstan / brms

Despite reading up on the subject, I can't wrap my head round it, so the question remains on shaky grounds, and responses along the lines of "read chapter x" are very welcome. What I'm doing is I'm ...
petyar's user avatar
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How to calculate WAIC from a JAGS model, and fix p_waic issue?

I am running a logistic regression type model in JAGS, and I noticed that I was getting different DIC scores (more than just a few points difference) between runs of the same model. I have a suspicion ...
HaplessEcologist's user avatar
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1 answer
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DIC, WAIC in JAGS

I have a Bayesian Hierarchical model using JAGS. In order to find the best model, I have compared the DIC of two models but It's not reliable. So, I decided to calculate WAIC from JAGS. However I have ...
Sirvan's user avatar
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13 votes
2 answers
3k views

Can WAIC be used to compare Bayesian linear regression models with different likelihoods?

I would like to use WAIC to help with model selection, where the models are simple linear regressions with Bayesian inference, non-flat priors and MCMC estimation. I am currently considering two such ...
Alex Ioannides's user avatar
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Scaling WAIC for Multiple Endogenous Response Variables

I'm trying to think about WAIC under a multivariate model scenario. Suppose I have one model composed of two relationships: y1 ~ x y2 ~ y1 This is one model. Now,...
jebyrnes's user avatar
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Warnings during WAIC computation: how to proceed?

I am computing the WAIC (widely applicable or Watanabe-Akaike information criterion) using the waic() function from the 'loo' ...
Jacob Socolar's user avatar