This paper reviews recent research on learning patterns of student teachers and
experienced teachers, mostly in the context of educational innovation and teachers' …

Built upon a 30-year dataset collected from the web of science database, the present
research aims to offer a comprehensive overview of papers, authors, streams of research …

We present the R package missMDA which performs principal component methods on
incomplete data sets, aiming to obtain scores, loadings and graphical representations …

Principal components analysis (PCA) is a well-known technique for approximating a tabular
data set by a low rank matrix. Here, we extend the idea of PCA to handle arbitrary data sets …

Poverty impacts people's choices and opportunities and can perpetuate a disadvantaged
status. Poverty remains a prevalent global issue due to disproportionate wealth distribution …

AIMS: Recent research has revealed that early life trauma (ELS), including abuse (sexual
and/or physical) and neglect, produce lasting changes in the CNS. We posited that cognitive …

In this paper we present the methodology of multidimensional scaling problems (MDS)
solved by means of the majorization algorithm. The objective function to be minimized is …

Clustering is a fundamental problem in many scientific applications. Standard methods such
as k-means, Gaussian mixture models, and hierarchical clustering, however, are beset by …

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 …

Mobile phone use is increasing in Sub-Saharan Africa, spurring a growing focus on mobile
phones as tools to increase agricultural yields and incomes on smallholder farms. However …