Is it possible that AIC = BIC?
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Two well-known (and related) measures of model complexity from statistics are the Akaike Information Criterion (AIC) and the Bayesian Information
Criterion (BIC).
When might AIC = BIC?
aic bic
New contributor
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add a comment |
$begingroup$
Two well-known (and related) measures of model complexity from statistics are the Akaike Information Criterion (AIC) and the Bayesian Information
Criterion (BIC).
When might AIC = BIC?
aic bic
New contributor
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8
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You should try writing down the formulas and setting them equal to each other :) You will get the answer immediately.
$endgroup$
– guy
11 hours ago
add a comment |
$begingroup$
Two well-known (and related) measures of model complexity from statistics are the Akaike Information Criterion (AIC) and the Bayesian Information
Criterion (BIC).
When might AIC = BIC?
aic bic
New contributor
$endgroup$
Two well-known (and related) measures of model complexity from statistics are the Akaike Information Criterion (AIC) and the Bayesian Information
Criterion (BIC).
When might AIC = BIC?
aic bic
aic bic
New contributor
New contributor
edited 10 hours ago
Richard Hardy
27.7k641128
27.7k641128
New contributor
asked 11 hours ago
JanJan
1311
1311
New contributor
New contributor
8
$begingroup$
You should try writing down the formulas and setting them equal to each other :) You will get the answer immediately.
$endgroup$
– guy
11 hours ago
add a comment |
8
$begingroup$
You should try writing down the formulas and setting them equal to each other :) You will get the answer immediately.
$endgroup$
– guy
11 hours ago
8
8
$begingroup$
You should try writing down the formulas and setting them equal to each other :) You will get the answer immediately.
$endgroup$
– guy
11 hours ago
$begingroup$
You should try writing down the formulas and setting them equal to each other :) You will get the answer immediately.
$endgroup$
– guy
11 hours ago
add a comment |
1 Answer
1
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As a reminder:
$$AIC = - 2 log mathcal{L}(hat{theta}|X)+2k $$
$$BIC = - 2 log mathcal{L}(hat{theta}|X)+k ln(n)$$
So for what values of $n$ is $2 = ln(n)$?
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3
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(+1) I noticed that for $BIC$ you write $log$ and $ln$ in the same expression. Is this distinction necessary?
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– Sycorax
5 hours ago
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Both logarithms have $e$ as their basis. It is just that log-likelihood (instead of ln-likelihood) is the term we use to describe the natural logarithm of the likelihood.
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– Stats
5 hours ago
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@Sycorax: I guess it's to signify that for the $log$ it really doesn't matter (as long as you're consistent) whereas for the $ln$, well it has to be $e$.
$endgroup$
– Mehrdad
10 mins ago
add a comment |
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1 Answer
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1 Answer
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oldest
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votes
$begingroup$
As a reminder:
$$AIC = - 2 log mathcal{L}(hat{theta}|X)+2k $$
$$BIC = - 2 log mathcal{L}(hat{theta}|X)+k ln(n)$$
So for what values of $n$ is $2 = ln(n)$?
$endgroup$
3
$begingroup$
(+1) I noticed that for $BIC$ you write $log$ and $ln$ in the same expression. Is this distinction necessary?
$endgroup$
– Sycorax
5 hours ago
$begingroup$
Both logarithms have $e$ as their basis. It is just that log-likelihood (instead of ln-likelihood) is the term we use to describe the natural logarithm of the likelihood.
$endgroup$
– Stats
5 hours ago
$begingroup$
@Sycorax: I guess it's to signify that for the $log$ it really doesn't matter (as long as you're consistent) whereas for the $ln$, well it has to be $e$.
$endgroup$
– Mehrdad
10 mins ago
add a comment |
$begingroup$
As a reminder:
$$AIC = - 2 log mathcal{L}(hat{theta}|X)+2k $$
$$BIC = - 2 log mathcal{L}(hat{theta}|X)+k ln(n)$$
So for what values of $n$ is $2 = ln(n)$?
$endgroup$
3
$begingroup$
(+1) I noticed that for $BIC$ you write $log$ and $ln$ in the same expression. Is this distinction necessary?
$endgroup$
– Sycorax
5 hours ago
$begingroup$
Both logarithms have $e$ as their basis. It is just that log-likelihood (instead of ln-likelihood) is the term we use to describe the natural logarithm of the likelihood.
$endgroup$
– Stats
5 hours ago
$begingroup$
@Sycorax: I guess it's to signify that for the $log$ it really doesn't matter (as long as you're consistent) whereas for the $ln$, well it has to be $e$.
$endgroup$
– Mehrdad
10 mins ago
add a comment |
$begingroup$
As a reminder:
$$AIC = - 2 log mathcal{L}(hat{theta}|X)+2k $$
$$BIC = - 2 log mathcal{L}(hat{theta}|X)+k ln(n)$$
So for what values of $n$ is $2 = ln(n)$?
$endgroup$
As a reminder:
$$AIC = - 2 log mathcal{L}(hat{theta}|X)+2k $$
$$BIC = - 2 log mathcal{L}(hat{theta}|X)+k ln(n)$$
So for what values of $n$ is $2 = ln(n)$?
answered 10 hours ago
StatsStats
50619
50619
3
$begingroup$
(+1) I noticed that for $BIC$ you write $log$ and $ln$ in the same expression. Is this distinction necessary?
$endgroup$
– Sycorax
5 hours ago
$begingroup$
Both logarithms have $e$ as their basis. It is just that log-likelihood (instead of ln-likelihood) is the term we use to describe the natural logarithm of the likelihood.
$endgroup$
– Stats
5 hours ago
$begingroup$
@Sycorax: I guess it's to signify that for the $log$ it really doesn't matter (as long as you're consistent) whereas for the $ln$, well it has to be $e$.
$endgroup$
– Mehrdad
10 mins ago
add a comment |
3
$begingroup$
(+1) I noticed that for $BIC$ you write $log$ and $ln$ in the same expression. Is this distinction necessary?
$endgroup$
– Sycorax
5 hours ago
$begingroup$
Both logarithms have $e$ as their basis. It is just that log-likelihood (instead of ln-likelihood) is the term we use to describe the natural logarithm of the likelihood.
$endgroup$
– Stats
5 hours ago
$begingroup$
@Sycorax: I guess it's to signify that for the $log$ it really doesn't matter (as long as you're consistent) whereas for the $ln$, well it has to be $e$.
$endgroup$
– Mehrdad
10 mins ago
3
3
$begingroup$
(+1) I noticed that for $BIC$ you write $log$ and $ln$ in the same expression. Is this distinction necessary?
$endgroup$
– Sycorax
5 hours ago
$begingroup$
(+1) I noticed that for $BIC$ you write $log$ and $ln$ in the same expression. Is this distinction necessary?
$endgroup$
– Sycorax
5 hours ago
$begingroup$
Both logarithms have $e$ as their basis. It is just that log-likelihood (instead of ln-likelihood) is the term we use to describe the natural logarithm of the likelihood.
$endgroup$
– Stats
5 hours ago
$begingroup$
Both logarithms have $e$ as their basis. It is just that log-likelihood (instead of ln-likelihood) is the term we use to describe the natural logarithm of the likelihood.
$endgroup$
– Stats
5 hours ago
$begingroup$
@Sycorax: I guess it's to signify that for the $log$ it really doesn't matter (as long as you're consistent) whereas for the $ln$, well it has to be $e$.
$endgroup$
– Mehrdad
10 mins ago
$begingroup$
@Sycorax: I guess it's to signify that for the $log$ it really doesn't matter (as long as you're consistent) whereas for the $ln$, well it has to be $e$.
$endgroup$
– Mehrdad
10 mins ago
add a comment |
Jan is a new contributor. Be nice, and check out our Code of Conduct.
Jan is a new contributor. Be nice, and check out our Code of Conduct.
Jan is a new contributor. Be nice, and check out our Code of Conduct.
Jan is a new contributor. Be nice, and check out our Code of Conduct.
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8
$begingroup$
You should try writing down the formulas and setting them equal to each other :) You will get the answer immediately.
$endgroup$
– guy
11 hours ago