Outlier detection with partial information:Application to emergency mapping

This paper, addresses the problem of novelty detection in the case that the observed data is a mixture of a known 'background' process contaminated with an unknown other process, which generates the outliers, or novel observations. The framework we describe here is quite general, employing univariate classification with incomplete information, based on knowledge of the distribution (the 'probability density function', 'pdf') of the data generated by the 'background' process. The relative proportion of this 'background' component (the 'prior' 'background' 'probability), the 'pdf' and the 'prior' probabilities of all other components are all assumed unknown. The main contribution is a new classification scheme that identifies the maximum proportion of observed data following the known 'background' distribution. The method exploits the Kolmogorov-Smirnov test to estimate the proportions, and afterwards data are Bayes optimally separated. Results, demonstrated with synthetic data, show that this approach can produce more reliable results than a standard novelty detection scheme. The classification algorithm is then applied to the problem of identifying outliers in the SIC2004 data set, in order to detect the radioactive release simulated in the 'oker' data set. We propose this method as a reliable means of novelty detection in the emergency situation which can also be used to identify outliers prior to the application of a more general automatic mapping algorithm. © Springer-Verlag 2007.

Response-based segmentation using Finite Mixture Partial Least Squares: theoretical foundations and an application to American Customer Satisfaction Index Data

When applying multivariate analysis techniques in information systems and social science disciplines, such as management information systems (MIS) and marketing, the assumption that the empirical data originate from a single homogeneous population is often unrealistic. When applying a causal modeling approach, such as partial least squares (PLS) path modeling, segmentation is a key issue in coping with the problem of heterogeneity in estimated cause-and-effect relationships. This chapter presents a new PLS path modeling approach which classifies units on the basis of the heterogeneity of the estimates in the inner model. If unobserved heterogeneity significantly affects the estimated path model relationships on the aggregate data level, the methodology will allow homogenous groups of observations to be created that exhibit distinctive path model estimates. The approach will, thus, provide differentiated analytical outcomes that permit more precise interpretations of each segment formed. An application on a large data set in an example of the American customer satisfaction index (ACSI) substantiates the methodology’s effectiveness in evaluating PLS path modeling results.

Experiments and observations on the behaviour and brain of the aging female mouse with special reference to dementia of the Alzheimer type

The objective of this research was to investigate the effects of normal aging and the additional effects of chronic exposure to two experimental diets, one enriched in aluminium, the other enriched in lecithin, on aspects of the behaviour and brain histology of the female mouse. The aluminium diet was administered in an attempt to develop a rodent model of Dementia of the Alzheimer Type (DAT). With normal aging, almost all assessed aspects of behaviour were found to be impaired. As regards cognition, selective impairments of single-trial passive avoidance and Morris place learning were observed. While all aspects of open-field behaviour were impaired, the degree of impairment was directly related to the degree of motoric complexity. Deficits were also observed on non-visual sensorimotor coordination tasks and in olfactory discrimination. Histologically, neuron loss, gliosis, vacuolation and congophilic angiopathy were observed in several of the brain regions/fibre tracts believed to contribute to the control of some of the assessed behaviours. The aluminium treatment had very selective effects on both behaviour and brain histology, inducing several features observed in DAT. Behaviourally, the treatment induced impaired spatial reference memory; reduced ambulation; disturbed olfactory function and induced the premature development of the senile pattern of swimming. Histologically, significant neuron loss and gliosis were observed in the hippocampus, entorhinal cortex, amygdala, medial septum, pyriform and pr-frontal cortex. In addition, the brain distribution of congophilic angiopathy was significantly increased by the treatment. The lecithin treatment had effects on both non-cognitive and cognitive aspects of behaviour. The effects of aging on open-field ambulation and rearing were partially ameliorated by the treatment. A similar effect was observed for single-trial passive avoidance performance. Age-dependent improvements in acquisition/retention were observed in 17-23 month mice and Morris place task performance was improved in 11 and 17 month mice. Histologically, a partial sparing of neurons in the cerebellum, hippocampus, entorhinal cortex and subiculum was observed.