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Lobotomy
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Hi, here's some information after fitting measurements to a lognormal distribution.
What exactely does it mean that the log likelyhood is -67.175?? As of my understanding the log likelihood, is the natural logaritm of the likelihood function, which is the probability that these measurements comes from this distribution??
1. is that correct?
2. why is it negative?
3. How can i decide if this is a good distribution fit? (graphically it looks satisfying, I am not in a need for extremely exact numbers for what I am going to use them for)
Distribution: Lognormal
Log likelihood: -67.175
Domain: 0 < y < Inf
Mean: 9.04552
Variance: 1.51012
Parameter Estimate Std. Err.
mu 2.19313 0.0208669
sigma 0.135233 0.0150259
Estimated covariance of parameter estimates:
mu sigma
mu 0.000435428 -2.49709e-018
sigma -2.49709e-018 0.000225778
edit: the likelihood, taking the exp of the log likelihood would be
exp(-67.175)= something*10^-30 ! incredibly small number. This can't be correct? the likelihood of that distribution can't be that small? the fit is not THAT bad =)
i would expect a likelihood of about 0.7-0.95 right? does anyone know what this number means?
What exactely does it mean that the log likelyhood is -67.175?? As of my understanding the log likelihood, is the natural logaritm of the likelihood function, which is the probability that these measurements comes from this distribution??
1. is that correct?
2. why is it negative?
3. How can i decide if this is a good distribution fit? (graphically it looks satisfying, I am not in a need for extremely exact numbers for what I am going to use them for)
Distribution: Lognormal
Log likelihood: -67.175
Domain: 0 < y < Inf
Mean: 9.04552
Variance: 1.51012
Parameter Estimate Std. Err.
mu 2.19313 0.0208669
sigma 0.135233 0.0150259
Estimated covariance of parameter estimates:
mu sigma
mu 0.000435428 -2.49709e-018
sigma -2.49709e-018 0.000225778
edit: the likelihood, taking the exp of the log likelihood would be
exp(-67.175)= something*10^-30 ! incredibly small number. This can't be correct? the likelihood of that distribution can't be that small? the fit is not THAT bad =)
i would expect a likelihood of about 0.7-0.95 right? does anyone know what this number means?
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