You can start by creating a custom probability distribution object that includes the necessary methods for calculating the negative log likelihood. Since you are using a power-law distribution, you've already implemented the logarithm of the probability density function (‘m...
In each simulation, the MLE of Z ∼ M S N ( η ) was obtained by maximizing the log-likelihood function: ℓ ( η ) = n 2 log ( 2 π ) − 1 2 ∑ i = 1 n z i 2 + ∑ i = 1 n log ζ 0 { η u ( z i ) } , (20) for shape parameter η and a random ...
Negative truncated log-likelihood functionLars SnipenKristian Hovde Liland
Generalized negative log likelihood and Viterbi algorithms
Log-likelihood function for the fixed-effects modelMaurizio ManuguerraGillian Heller