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AIC stands for the Akaike Information Criterion, which is one technique used to select the best model from a class of models using a penalized likelihood. A smaller AIC implies a better model.
7
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1
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Comparing differences of AIC of different data sets
The conclusion might not be valid because the AIC values are calculated on different data sets and therefore might not be comparable. … However, since actually AIC differences are compared the conclusion might be valid. What is your take on this? …
2
votes
1
answer
800
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Calculation AIC without loglikelihood-function
I want to calculate the AIC without calculating the loglikelihood-function (which seems complicated). … : ",AIC(l)))
print(paste("aic_s: ",aic_self))
The script returns:
Shapiro-Wilk normality test
data: l.resi
W = 0.9845, p-value = 0.1046
[1] "aic: 520.121593704369"
[1] "aic_s: 109.467296141423 …
3
votes
2
answers
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Model selection using mean AIC for very huge data sets
If this is the case, is the following a reasonable approach:
Fit each model to $n$ smaller random subsets of the original data set and calculate the mean AIC. … Then, select the model with the lowest mean AIC. …
5
votes
2
answers
14k
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Is AIC a measure of goodness of fit? [duplicate]
The wikipeda-page for AIC states:
"it (AIC) deals with the trade-off between the goodness of fit of the model and the complexity of the model". … I interpret this that AIC is considered a measure of goodness of fit.
So, is AIC a measure of goodness of fit or not? …
8
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1
answer
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How can I calculate the AICc if the number of samples equals the number of parameters plus one
The formula for the AICc is:
AICc = AIC - 2k(k+1) / (n-k-1)
where k is the number of parameters and n the number of samples.
Is it somehow possible to calculate the AICc for n=k+1? …
4
votes
1
answer
909
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What is the number of parameters for AIC if some coefficients are zero?
Does this coefficient count as a parameter when calculating the AIC? …
18
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2
answers
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Number of parameters in an artificial neural network for AIC
How can I calculate the number of parameters in an artificial neural network in order to calculate its AIC? …
6
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0
answers
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When should I use AIC instead of cross-validation?
Thus, when should I use AIC instead? …
3
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0
answers
408
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What is the number of parameters of an elastic net model?
I want to calculate the AIC of an elastic net model but how do I calculate the number of parameters? Is it simply the number of independent variables plus one? …
14
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1
answer
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AIC of ridge regression: degrees of freedom vs. number of parameters
When it comes to ridge regression I read that the trace of the hat matrix -- the degree of freedom (df) -- is simply used as the number of parameters term in the AIC formula (e.g. here or here). …
4
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0
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Using AIC or cross-validated MSE for selecting neural network models for time series prediction
However, the first model yields the lower AIC, probably because it has less parameters (I calculated the likelihood function of the models using the number of samples and the MSE). … AIC says the first model, CV MSE the second one. …