Linked Questions
48 questions linked to/from Is there any reason to prefer the AIC or BIC over the other?
7
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2
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When do you use AIC vs. BIC [duplicate]
How do you know when to use AIC or BIC for determining model fit? Is it just a judgment call? Is there an intuitive explanation as to which heuristic is better than the other?
7
votes
1
answer
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Use BIC or AIC as approximation for Bayesian Model Averaging [duplicate]
I want to compare "real" Bayesian Model Averaging (BMA) performed with the EM algorithm and information-criterion based BMA.
Which one, BIC or AIC, is a "closer" approximation to the "real" BMA?
BIC ...
1
vote
0
answers
802
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Interpretation of AIC, BIC and KIC [duplicate]
Possible Duplicate:
Is there any reason to prefer the AIC or BIC over the other?
Can anyone please interpret each term in AIC, BIC and KIC. And the difference between the three.
Thanks in ...
0
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0
answers
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Optimal number of components in a beta mixture model [duplicate]
This is a well-written blog on how we can fit a mixture of beta distributions to a dataset:
http://varianceexplained.org/r/mixture-models-baseball/
However, it would have been excellent to identify ...
117
votes
12
answers
70k
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When should linear regression be called "machine learning"?
In a recent colloquium, the speaker's abstract claimed they were using machine learning. During the talk, the only thing related to machine learning was that they perform linear regression on their ...
51
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5
answers
227k
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AIC guidelines in model selection
I typically use BIC as my understanding is that it values parsimony more strongly than does AIC. However, I have decided to use a more comprehensive approach now and would like to use AIC as well. I ...
11
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5
answers
7k
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Is a variable significant in a linear regression model?
I've got a linear regression model with the sample and variable observations and I want to know:
Whether a specific variable is significant enough to remain included in the model.
Whether another ...
23
votes
2
answers
10k
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Why is best subset selection not favored in comparison to lasso?
I'm reading about best subset selection in the Elements of statistical learning book.
If I have 3 predictors $x_1,x_2,x_3$, I create $2^3=8$ subsets:
Subset with no predictors
subset with predictor $...
25
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4
answers
864
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Addressing model uncertainty
I was wondering how the Bayesians in the CrossValidated community view the problem of model uncertainty and how they prefer to deal with it? I will try to pose my question in two parts:
How important ...
26
votes
2
answers
11k
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Best approach for model selection Bayesian or cross-validation?
When trying to select among various models or the number of features to include for, say prediction I can think of two approaches.
Split the data into training and test sets. Better still, use ...
33
votes
1
answer
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Proof of LOOCV formula
From An Introduction to Statistical Learning by James et al., the leave-one-out cross-validation (LOOCV) estimate is defined by $$\text{CV}_{(n)} = \dfrac{1}{n}\sum\limits_{i=1}^{n}\text{MSE}_i$$
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35
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4
answers
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AIC versus cross validation in time series: the small sample case
I am interested in model selection in a time series setting. For concreteness, suppose I want to select an ARMA model from a pool of ARMA models with different lag orders. The ultimate intent is ...
13
votes
4
answers
66k
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Interpretation of AIC value
Typical values of AIC that I have seen for logistic models are in thousands, at least hundreds.
e.g. On http://www.r-bloggers.com/how-to-perform-a-logistic-regression-in-r/
the AIC is 727.39
While ...
14
votes
4
answers
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Are models identified by auto.arima() parsimonious?
I have been trying to learn and apply ARIMA models. I have been reading an excellent text on ARIMA by Pankratz - Forecasting with Univariate Box - Jenkins Models: Concepts and Cases. In the text the ...
11
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3
answers
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What is AIC? Looking for a formal but intuitive answer
I've heard that AIC can be used to choose among several models (which regressor to use).
But i would like to understand formally what it is in a kind of "advanced undergraduated" level, which I ...