Metabolomics is the comprehensive study of small molecule metabolites in biological
systems. By assaying and analyzing thousands of metabolites in biological samples, it …

To achieve scientific progress in terms of building a cumulative body of knowledge, careful
attention to benchmarking is of the utmost importance, requiring that proposals of new …

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 …

Data with mixed-type (metric–ordinal–nominal) variables are typical for social stratification,
ie partitioning a population into social classes. Approaches to cluster such data are …

The demands and pressures during the first study year at university are likely to arouse a
variety of emotions among students. Nevertheless, there are very few studies on the role of …

Clustering methods are often used to model energy consumption for two reasons. First,
clustering is often used to process data and to improve the predictive accuracy of …

Corporate sustainable innovation is a major driver of institutional change, and its success
can be largely attributed to employees. While some scholars have described the importance …

Abstract Model-based clustering is a popular approach for clustering multivariate data which
has seen applications in numerous fields. Nowadays, high-dimensional data are more and …

In recent years, trajectory approaches to characterizing individual differences in the onset
and course of substance involvement have gained popularity. Previous studies have …

Survey data frequently serve as the basis for market segmentation studies. Survey data,
however, are prone to a range of biases. Little is known about the effects of such biases on …