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Given a random variable $X$ which arise from a parameterized distribution $F(X;θ)$, the likelihood is defined as proportional to the probability of observed data as a function of $θ$: $\operatorname{L}(θ | x)=\operatorname{P}(X=x \mid θ)$
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Fitting of bivariate data to a self-defined probability density function
I would wish to fit it via method of maximum likelihood, but my density function has 2 infinite sums in it so strictly speaking I don't have a closed form expression. … Thus, for a given set of bivariate data and a self-defined bivariate density function, I wish to estimate 5 parameters via the method of maximum likelihood.
Hoping someone can help me :) …