Special issue on data analysis and classification in marketing - preface by the guest editors

Guest Editors’ Preface Special Issue on Reversible Computing

Special Issue on Qualitative Approaches to E-marketing and Online Consumer Behaviour: Guest Editors' Introduction

Inma Rodríguez-Ardura Gerard Ryan Ulrike Gretzel Special Issue on Qualitative Approaches to E-marketing and Online Consumer Behaviour: Guest Editors’ Introduction Journal of Theoretical and Applied Electronic Commerce Research ISSN 0718–1876 Electronic Version VOL 7 / ISSUE 2 / AUGUST 2012 / IV-V © 2012 Universidad de Talca Chile This paper is available online at www.jtaer.com DOI: 10.4067/S071...

Special issue on "New trends on model-based clustering and classification" - Preface by the Guest Editors: Salvatore Ingrassia, Geoffrey J. McLachlan, Gérard Govaert

This Special Issue of ADAC is devoted to recent developments in Model-Based Clustering and Classification which is an increasingly active area in both theoretical and applied research. This area has attracted the interest of a growing number of researchers due to the high potential of such approaches in applications, and new different topics have been investigated by several authors. The Call f...

Special Issue on Robust Methods for Classification and Data Analysis - Preface by the Guest Editors

It is now widely recognized that most statistical techniques are not resistant to outliers or other deviations from the classical assumptions. Therefore, the development of highly robust and efficient statistical methods has become a goal of paramount importance in both theoretical and applied statistics. The demand for such methods has been driven by the increasing availability of data in almo...

Preface INTRODUCTION TO THE SPECIAL ISSUE ON CAUSAL DISCOVERY

Many empirical sciences, including the social sciences and life sciences, aim to study causal relationships. Researchers in these fields need computational methods for analyzing observed data and identifying causal structures among a set of variables. Such computational methods enable researchers to draw conclusions on the basis of both their assumptions and the observed data. Moreover, these m...