More specifically this is the sample proportion of the seeds that germinated. Where L m denotes the likelihood of the respective model either Model 1 or Model 2 and l o g l i k m the natural log of the models final likelihood ie the log likelihood. The log-likelihood function is typically used to derive the maximum likelihood estimator of the parameter.
Li f k Li pk pk f k 1 pkpk 1 pk pk 1 L i f k L i p k p k f k 1 p k p k 1 p k p k 1 And thus we have differentatied the negative log likelihood with respect to the softmax layer.
Thus S x i p n and 1nS x i p. The log-likelihood function Ftheta is defined to be the natural logarithm of the likelihood function Ltheta. First write the probability density function of the Poisson distribution. However the result of likelihood value is not same result which I was using Weilbull distribution.