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2 votes

Why is everything based on likelihoods even though likelihoods are so small?

The absolute value of a likelihood is meaningless as discussed here: Is the exact value of any likelihood meaningless? The likelihood function is also not the same as a probability distribution and it ...
Sextus Empiricus's user avatar
0 votes

Parameterization of Negative Binomial for Dynamical System Model Calibration/Fitting

Checking ?dnbinom, the equivalent parameterisation is: your $d$ is R's x, your $p$ is R's ...
Alex J's user avatar
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3 votes

Why is everything based on likelihoods even though likelihoods are so small?

If you flip a coin which is known to be weighted $100$ times and it comes up heads $80$ times, then you probably have a guess as to what the weight might be. One way to formalize this intuition is to ...
Steven Gubkin's user avatar
9 votes

Why is everything based on likelihoods even though likelihoods are so small?

First, as others have mentioned, we usually work with the logarithm of the likelihood function, for various mathematical and computational reasons. Second, since the likelihood function depends on the ...
Durden's user avatar
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24 votes

Why is everything based on likelihoods even though likelihoods are so small?

The key lies not in the absolute size of the likelihood values but in their relative comparison and the mathematical principles underlying likelihood-based methods. The smallness of the likelihood is ...
ADAM's user avatar
  • 504
5 votes

Why is everything based on likelihoods even though likelihoods are so small?

I can think of two things that might help you. First, likelihoods are defined only to a proportionality factor and their utility comes from their use in a ratio and while they are proportional to the ...
Michael Lew's user avatar
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2 votes

Interpreting AIC relative likelihoods ( qpcR::akaike.weights() )

Generally: Relative likelihoods are relative. There is no reason that I can see for them to add to anything and setting one of them to 1 is arbitrary, but useful, as it lets us get a sense of the size ...
Peter Flom's user avatar
  • 116k
2 votes

Compare failure rates across multiple systems

I present a second analysis using a Bayesian hierarchical model to estimate the failure probabilities of the seven sets as well as the mean failure probability in the population of sets. The ...
dipetkov's user avatar
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