# Questions tagged [bic]

BIC is an acronym for Bayesian Information Criterion. BIC is one method of model comparison. See also AIC

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### Is BIC asymptotically efficient for minimizing prediction error if the true model is being considered?

If a set of models is being compared using BIC and AIC, given the fact that the true model (the one which generated the data) is in this set (and given the other assumptions that guarantee BIC ...
0answers
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### Problems with training a discriminative model with generative methods

I'm reading Friedman, Geiger and Goldszmidt's 1997 paper "Bayesian Network Classifiers". On page 7, they discuss the problems with using methods for learning generative models (specifically ...
1answer
64 views

### Calculating AIC & BIC

I have an output from two LMER-models and I'd like to calculate AIC & BIC. I believe I've understood the tables correctly, but I'm uncertain regarding the k parameter; have I understood it ...
0answers
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### Log Likelihood for Two Stage Least Squares (for AIC or BIC)

I'm looking to use a number of information criteria (BIC, AIC, etc.) for Two Stage Least Squares. Of course all information criteria need a log likelihood - and I'm also aware that for a Log-...
0answers
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### BIC for combined model selection on independent data sets (BIC not additive)

I have two statistically independent data sets, $x_1$ and $x_2$, both of size $n$, and I would like to select a model $m$ out of the same candidate set $\{1 \ldots M\}$ for each of them, i.e. I select ...
1answer
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### Selecting a model for linear regression: adjusted metrics (BIC, AIC, adjusted R2 etc…) on training set or validation/crossvalidation using test set?

Linear regression has model hyperparameters such as number of predictors. For example in a autoregressive time series model AR(p), p is the number of predictors. To find which value of p to find we ...
0answers
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### Application of BIC when using data to estimate hyperparameters

I plan on using the following equation to calculate the Bayesian information criterion of various linear models applied to the same dataset: $n\ln(RSS/n) + k\ln(n)$ (I believe this equation applies ...
0answers
51 views

### negative values for AIC and BIC

I am trying to fit a gumbel distribution using MLE for the following 10 data points. DATA=(3.62,3.76,3.57,3.56,3.61,3.77,3.46,3.6,3.39,3.74) The problem is that the ...
0answers
27 views

### Picking a suitable performance metric when comparing the same model but using different sets of training data (Causal inference model)

I am comparing the same models prediction accuracy (Causal Impact) using different control variables as predictors and looking for a metric to decide which set of controls to use. Reading into AIC and ...
0answers
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### BIC and RMSE are Contradict each other for ARIMA Model Selection using R: Do I Err in Theory or in Practice?

I was surprised to see that RMSE and BIC have contradictory trends for the same time-series data. EDITED The procedures in my code are: simulate a 15 AR series of ...
2answers
56 views

### Bayes Information Criterion — what does log mean?

Super basic question about the BIC — is it defined in terms of log base ten or the natural logarithm? I see the latter on Wikipedia; but see ‘log’ not ‘ln’ in the original paper (though am aware that ...
1answer
220 views

### How to calculate AIC and BIC?

I should find formula of BIC and AIC which is used in statsmodels. I have array with values: ...
0answers
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### How can I determine what value of k to use for an AIC/BIC of a fractional power equation?

I have two equations of which I am trying to determine which is the better fit using AIC and BIC: a quadratic equation of the formula $$\ y = β_{1}x^2+β_{2}x+β_{0}$$ and a fractional power equation ...
1answer
79 views

### Validity of BIC for Dirichlet process mixture models

I am implementing clustering using Dirichlet process mixture models via scikit learn's Variational Bayesian Gaussian Mixture model. I arrived at the appropriate priors iteratively, and I am able to ...
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75 views

### LASSO Regression with AIC or BIC as Model Selection Criterion

I am fitting a linear model using LASSO and exploring BIC (or AIC) as the selection criterion. The most useful resource I have stumbled upon is this earlier question here on CrossValidated: Is it ...
0answers
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### AIC and BIC for wrong models! [closed]

If the models we consider for the data are wrong, what happens to the model selection with AIC or BIC as the data increases? Any hint?
1answer
42 views

### How do I find Schwartz criterion (or Bayesian Information Criterion) for these three models?

I have to find the schwarz criterion for each of the models in this maths question using RStudio but I don't know where to start. I know I need to find the free parameters but don't know how to find ...
1answer
377 views

### Can I use AIC/BIC to compare a Poisson model to a negative Binomial model?

I would please like to enquire if it's appropriate for me to compare the fit of a Poisson vs. a negative Binomial model for my data, given that the two models are nested, i.e. the negative Binomial ...
0answers
19 views

### Model fit across methods

I have one dataset and I would like to compare analytic methods. The data have to do with risk factors predicting functioning in multiple domains (multiple IVs, multiple DVs). All variables are ...
0answers
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### BIC for mixed continuous and discrete parameters?

I am interested in doing a BIC analysis for models which have mixed continuous and discrete variables. To give a minimalistic example which captures the relevant structure, let $\theta\in\mathbb{R}^2$ ...
1answer
46 views

### Conjectures regarding EM approximations of mixtures of multivariate normal distributions

Consider $X\in\mathbb{R}^{N\times d}$ containing data for $N$ points in $d$ dimensions drawn from a bimodal multivariate normal distribution, where any row $x$ of $X$ follows the mixed multivariate ...
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### How to use BIC (Bayesian Information Criterion) if the data are not identically distributed but rely on other covariate?

I'm now constructing some models and would like to compare and select the models. I read the wikipedia and some slides about BIC, then I found the ML(maximum likelihood) part in BIC seems to be based ...
1answer
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### How to get log-likelihood from squared deviance in Scikit Learn

The score() function computes D^2, the percentage of deviance explained, but I'd like to get the log-likelihood to calculate BIC. What's the formula to go from deviance to log-likelihood? Score ...
1answer
32 views

### Test to select best models in production

I've got four models in production and using the average of them as the served prediction. We get ground truth data immediately. I've optimized them and found the best models during my training/...
1answer
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### AIC/BIC vs the rule of “must include lower order interaction”

I am running a series of mixed effect models, which include both linear and quadratic term of a variable T (continuous) and the main IV I (categorical), and facing a dilemma. Model 2 include ...
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### BIC-Lasso Shrinkage

I am currently reviewing the below paper and was wondering if it was possible to correctly implement the BIC equation for "BIC-LASSO Shrinkage". This doesn't appear to be the same as the typical BIC ...
1answer
260 views

### Where is the divide between information criterion (AIC, BIC, etc…) and cross validation?

I've taken a regression class and am now in a machine learning class. In regression, we talk about model selection using adj-R2 and AIC/BIC. In my machine learning class, we primarily select models ...
1answer
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### How to perform model selection with the BIC for correlated observations

How is it possible to use the Bayesian Information Criterion (and more generally, to perform model selection) when observations are correlated ? I would like to compare the BIC of different models ...
0answers
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### BIC/AIC Optimal Values

I was reading this paper (https://dms.umontreal.ca/~augusty/FHMV_paper.pdf) and noticed in their analysis (specifically Tables 2 and 3), the highest AIC and BIC values are highlighted and used as ...
1answer
59 views

### Should I compare two models using AIC?

I calculated duration (IV) in seconds using two different ranges (0 to 5s and 0 to 10s). The aim was to find out which range contributes to higher word learning outcomes (dichotomous DV). I ...