There is an intense and partly recent literature focussing on the problems of selecting the bandwidth parameter for kernel density estimators. Available methods are largely 'very nonparametric', in the sense of not requiring ...

Suppose that a sequence of data points follows a distribution of a certain parametric form, but that one or more of the underlying parameters may change over time. This paper addresses various natural questions in such a ...

Independent data are efficiently integrated by adding their respective log-likelihoods. Instead of Bayesian updating of information, We propose to use the likelihood directly as a vehicle for coherent learning. If past ...