The paper makes a critical assessment of Aitchison's criterion of density estimation. It seems not to satisfy certain intuitive requirements. A new criterion based on decisions theoretic considerations is introduced. It is shown through examples that the judgement about the choice of density estimates is seriously dependent on the criterion chosen. Some other density estimates are introduced which look similar to Bayesian predictive density estimates without using a prior distribution.
Abstract We describe and illustrate Bayesian inference in models for density estimation using mixtures of Dirichlet processes. These models provide natural settings for density ...
Abstract Advances in computation and the fast and cheap computational facilities now available to statisticians have had a significant impact upon statistical research, and espe...
▪ Abstract Although covariance structure analysis is used increasingly to analyze nonexperimental data, important statistical requirements for its proper use are frequently igno...
Summary A technique for using kernel density estimates to investigate the number of modes in a population is described and discussed. The amount of smoothing is chosen automatic...
Abstract Selecting an appropriate set of confounders for which to control is critical for reliable causal inference. Recent theoretical and methodological developments have help...
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