Signal Processing Methods for Music Transcription is the first book dedicated to uniting
research related to signal processing algorithms and models for various aspects of music …

Cluster analysis finds groups in data automatically. Most methods have been heuristic and
leave open such central questions as: how many clusters are there? Which method should I …

Group-level variance estimates of zero often arise when fitting multilevel or hierarchical
linear models, especially when the number of groups is small. For situations where zero …

In the past ten years there has been a dramatic increase of interest in the Bayesian analysis
of finite mixture models. This is primarily because of the emergence of Markov chain Monte …

Variable selection in clustering analysis is both challenging and important. In the context of
modelbased clustering analysis with a common diagonal covariance matrix, which is …

The paper considers the problem of multiple testing under dependence in a compound
decision theoretic framework. The observed data are assumed to be generated from an …

Clustering remains a vibrant area of research in statistics. Although there are many books on
this topic, there are relatively few that are well founded in the theoretical aspects. In Robust …

Given distinct climatic periods in the various facets of the Earth's climate system, many
attempts have been made to determine the exact timing of 'change points' or regime …

When fitting hierarchical regression models, maximum likelihood (ML) estimation has
computational (and, for some users, philosophical) advantages compared to full Bayesian …

High dimensionality causes problems in various areas of statistics. A particular situation that
rarely has been considered is the testing of hypotheses about multivariate regression …