What are some situations where a mixture of binomial distributions might be a more appropriate model?

Jul 6, 2006 ... A model of Markov dependent trials is considered that leads to a generalization of the binomial distribution in the context of evaluating ... The negative binomial distribution. RA Fisher FRS, RA Fisher FRS. Search for more papers by this author. First published: January 1941. Mar 19, 2021 ... Using a binomial GLMM, we could model the probability of eating vegetables daily given various predictors such as sex of the student, race of ... Abstract. The statistical method of motor unit number estimation (MUNE) uses the natural stochastic variation in a muscle's compound response to electrical ... Dec 1, 1996 ... The statistical distributions of the counts of organisms are generally skewed, and hence not normally distributed, nor are variances ... Oct 20, 2023 ... Proof: Kullback-Leibler divergence for the binomial distribution ... P:X∼Bin(n,p1)Q:X∼Bin(n,p2).(1) (1) P : X ∼ B i n ( n , p 1 ) Q : X ∼ B i n ( ... Binomial Distribution X∼Bin(n,p) ; n= p= ; x=. Aug 21, 2024 ... Binomial distribution is a fundamental concept that finds extensive application in machine learning. From binary classification to hypothesis ... Normal distribution describes continuous data which have a symmetric distribution, with a characteristic 'bell' shape. May 16, 2018 ... Poisson-binomial distribution - any existing Stan implementation? · works on the log scale for arithmetic stability · is quadratic in the size ...