Sparse principal component analysis is a very active research area in the last decade. It produces component loadings with many zero entries which facilitates their interpretation and helps avoid redundant variables. The classic factor analysis is another popular dimension reduction technique which shares similar interpretation problems and could greatly benefit from sparse solutions. Unfortuna...

This paper develops and applies a Bayesian approach to Exploratory Factor Analysis that improves on ad hoc classical approaches. Our framework relies on dedicated factor models and simultaneously determines the number of factors, the allocation of each measurement to a unique factor, and the corresponding factor loadings. Classical identification criteria are applied and integrated into our Bay...

We present a novel unsupervised artificial neural network for the extraction of common features in multiple data sources. This algorithm, which we name Exploratory Correlation Analysis (ECA), is a multi-stream extension of a neural implementation of Exploratory Projection Pursuit (EPP) and has a close relationship with Canonical Correlation Analysis (CCA). Whereas EPP identifies ”interesting” s...

Cover The words on the front and back cover pages have been ordered by letting MATLAB ® choose randomly and uniformly from a list of selected keywords. i Preface This PhD dissertation is based on a series of research projects conducted at The Royal Veterinary and Agricultural University (KVL), in the Chemometrics Research Group of Professor Lars Munck and colleagues during the period 1996-99. P...

Bi-factor analysis is a form of confirmatory factor analysis originally introduced by Holzinger. The bi-factor model has a general factor and a number of group factors. The purpose of this paper is to introduce an exploratory form of bi-factor analysis. An advantage of using exploratory bi-factor analysis is that one need not provide a specific bi-factor model a priori. The result of an explora...

Despite the importance of exploratory data analysis (EDA) in statistics and science, few people have worked on its philosophical foundations. In psychology, the present author (Haig, 2012; Behrens et al., 2013) have commented on philosophical aspects of EDA. They hold contrasting views about the appropriateness of abductive reasoning as a core component of the philosophy of EDA. Behrens and his...

Chapter Overview In this chapter, an introductory description of the exploration of genomic data is given. Rather than attempt an exhaustive overview of the types of genomic data and methods of analysis, the chapter focuses on one type of data, gene expression profiling by microarray technology, and one method of analysis, cluster analysis for discovering and sorting mixed populations. This typ...

This study has been carried out to develop a critical checklist for global/commercial textbooks which play a crucial role in language teaching/learning. For this aim, a number of items have been developed based on a comprehensive review of the related literature and experts’ opinions. The tentative checklist was administered to the targeted population, yet 326 checklists were deemed appropriate...