Probabilistic models, such as hidden Markov models or Bayesian networks, are commonly used to model biological data. Much of their popularity can be attributed to the existence of efficient and robust ...

Series B (Statistical Methodology) of the Journal of the Royal Statistical Society started out simply as the Supplement to the Journal of the Royal Statistical Society in the Society's centenary year ...

The evolution of DNA sequences can be described by discrete state continuous time Markov processes on a phylogenetic tree. We consider neighbor-dependent evolutionary models where the instantaneous ...

The AIC statistic is widely used to select the best model among alternative parametric models. The minimum AIC model selection procedure can be interpreted as a maximization of the expected entropy ...

This paper develops a new scheme for improving an approximation method of a probability density function, which is inspired by the idea in the Hilbert space projection theorem. Moreover, we apply ...