The following mixture model-based clustering methods are compared in a simulation study with one-dimensional data, fixed number of clusters and a focus on outliers and uniform “noise”: an ML-estimator (MLE) for Gaussian mixtures, an MLE for a mixture of Gaussians and a uniform distribution (interpreted as “noise component” to catch outliers), an MLE for a mixture of Gaussian distributions where...

Borderline personality disorder (BPD) involves disruptions in attachment, self, and self-regulation, domains conceptually similar to developmental tasks of early childhood. Because offspring of mothers with BPD are at elevated risk of developing BPD themselves (White, Gunderson, Zanarini, & Hudson, 2003), studying them may inform precursors to BPD. We sampled 31 children age 4-7 whose mothers h...

Most research on adult attachment is based on the assumption that working models are relatively general and trait-like. Recent research, however, suggests that people develop attachment representations that are relationship-specific, leading people to hold distinct working models in different relationships. The authors report a measure, the Relationship Structures questionnaire of the Experienc...

Discontinuous increases in the net accumulation of cellular phospholipid were previously observed during the synchronous growth of Rhodopseudomonas sphaeroides (Lueking, D. R., Fraley, R. T., and Kaplan, S. (1978) J. Biol. Chem. 253, 451-457). This pattern is shown to result from large increases in the rate of phospholipid synthesis, occurring just prior to cell division. The absence of detecta...

Here we present a sensitivity analysis to evaluate several computational approaches to obtain an estimate of the maximum a priori (MAP) partition in the Dirichlet process mixture model framework. Specifically, we use simulated data from mixtures of normals to compare an agglomerative greedy search algorithm [Ward Jr, 1963, Wang and Dunson, 2011], a Polya urn Gibbs sampling scheme [MacEachern, 1...

A classification method is developed to classify samples when both labelled and unlabelled samples are available. The classification rule is estimated using both the labelled and unlabelled data, in contrast to many classical methods which only use the labelled data for estimation. This methodology models the data as arising from a Gaussian mixture model with parsimonious covariance structure, ...

Ainsworth's description of attachment patterns in the Strange Situation is one of the best known and most enduring descriptive insights in developmental psychology. In view of the importance of the Avoidant, Secure, Resistant (ABC) classification system to attachment theory and research, it is surprising that attachment theorists have paid so little attention to whether these categories represe...

ML-estimation based on mixtures of Normal distributions is a widely used tool for cluster analysis. However, a single outlier can make the parameter estimation of at least one of the mixture components break down. Among others, the estimation of mixtures of t-distributions by McLachlan and Peel [Finite Mixture Models (2000) Wiley, New York] and the addition of a further mixture component accoun...

Booth-LaForce and Roisman's monograph on the Adult Attachment Interview (AAI) featured a taxometric analysis to determine whether variation along two components, dismissing and preoccupied states of mind, was categorical or dimensional. Empirically evaluating the latent structure of these constructs helps to avoid spurious categories or dimensions. This benefits researchers working with measure...

MOTIVATION Inner holes, artifacts and blank spots are common in microarray images, but current image analysis methods do not pay them enough attention. We propose a new robust model-based method for processing microarray images so as to estimate foreground and background intensities. The method starts with a very simple but effective automatic gridding method, and then proceeds in two steps. Th...