We specify a class of Gaussian rank-r latent models for cross-covariance. We show by construction that any variance-covariance matrix for the observed variables induced by rank-r reduced-rank regression can be induced by a rank-r latent model. 1 Model specification Basic terms are introduced which will be used to state the result. 1.1 Rank-r constraint models Let p be the number of X-variables ...

The segmentation of Spanish spirant approximant consonants poses several methodological challenges given the gradual transition from these consonants to neighbouring segments. Most studies to date employ manual segmentation approaches, although these methods are highly subjective and time-consuming. Alternative automated approaches have used the minimum intensity in the consonant and maxima fro...

Many algorithms have been proposed for the machine learning task of classification. One of the simplest methods, the naive Bayes classifier, has often been found to give good performance despite the fact that its underlying assumptions (of independence and a normal distribution of the variables) are perhaps violated. In previous work, we applied naive Bayes and other standard algorithms to a br...