Editorial Journal of Classification 34:36 1-36 5 (2017) DOI: 10.1007/s00357- -0 1 7-92 45 -7 This third issue of Volume 34 covers a lot of ground. As usual, there are a wide range of theoretical papers that are based on a bevy of tried and true multivariate techniques. However, there are also some unique aspects to this issue that would be welcome to expand upon in future issues as it provides a healthy and vibrant variability to the Journal of Classification: (1) the first paper focused exclusively on Bayesian techniques that have appeared in some years, (2) two application papers that integrate multiple multivariate and classification approaches to solve extremely useful “real-world” problems, and (3) the first software package that has appeared in several volumes. I discuss each of these in turn, and then conclude with a short paragraph outlining a specific project that I have begun to pursue that will flesh out some of the history of the content of the Journal of Classification. The first paper in the final issue of 2017 is by A.P. Zubarev and addresses the nature of the ultrametric that can be generated from a random distribution of points in Euclidean space when the http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Classification Springer Journals


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Copyright © 2017 by Classification Society of North America
Statistics; Statistical Theory and Methods; Pattern Recognition; Bioinformatics; Signal,Image and Speech Processing; Psychometrics; Marketing
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