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AIC calculation in Mathematica

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Hi Rohit Thank you for your answer and the link to the documentation. However, this definition does not correspond to the simple formula used by Mathematica to compute the AIC value based on the residual sum of squares of the fit. I cannot refer in my paper to a magical way of calculating the AIC value.

Posted 5 years ago

Hi Stéphane,

From the documentation here.

"AIC" and "BIC" are likelihood-based goodness-of-fit measures. Both are equal to -2 times the log-likelihood for the model plus k p, where p is the number of parameters to be estimated including the estimated variance. For "AIC" k is 2, and for "BIC" k is log(n).

POSTED BY: Rohit Namjoshi
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