Many recent approaches to modeling social networks have focussed on embedding
the actors in a latent “social space”. Links are more likely for actors that are
close in social space than for actors that are distant in ...
The purpose of this paper is to develop a stock selection algorithm with similar properties as Cover’s Universal Portfolio, but providing superior early growth. Cover’s Universal Portfolio generates a growth rate asymptotically ...
Applicants to degree courses in Irish colleges and universities rank up to ten degree courses from a list of over five hundred. These data provide a wealth of
information concerning applicant degree choices. A Dirichlet ...
The p* model is widely used in social network analysis. The likelihood of a network under this model is impossible to calculate for all but trivially small networks. Various approximation have been presented in the literature, ...
Statistical spatial repeatability (SSR) is an extension to the well known concept of spatial repeatability. SSR states that the mean of many patterns of dynamic tyre force applied to a pavement surface is similar for a ...
Food authenticity studies are concerned with determining if food samples have been correctly labelled or not. Discriminant analysis methods are an integral part of the methodology for food authentication. Motivated by food ...
A new family of mixture models for the model-based clustering of longitudinal data is introduced.
The covariance structures of eight members of this new family of models are given and the associated maximum likelihood ...
Background:
Data from metabolomic studies are typically complex and high-dimensional. Principal component analysis (PCA) is currently the most widely used statistical technique for analyzing metabolomic data. However, ...
Given that one of the children in a two-child family is a boy, what are the chances that the other is also a boy. The intuitive answer is 50 : 50. More careful investigation leads us to a 1-in-3 chance. We investigate ...
In recent years, work has been carried out on clustering gene expression microarray data. Some approaches are developed from an algorithmic viewpoint whereas others are developed via the application of mixture models. In ...