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New Issues and Paradigms in Research on Social Dilemmas
This edited volume has been compiled to present new theoretical and methodological developments in the field of social dilemma research. Social dilemmas are situations when there is a conflict between self-interest and collective interest. Research in this area has gained interest in the last twenty years in disciplines such as sociology, psychology, and economics. It also has wide applications to numerous real-world issues including environmental degradation, organizational management, and provision of societal public good. The three sections in the volume mirror the different levels of analysis in this research: the individual, group, and societal levels.
New Developments in Classification and Data Analysis ; Proceedings of the Meeting of the Classification and Data Analysis Group (CLADAG) of the Italian Statistical Society, University of Bologna, September 22-24, 2003
This volume contains revised versions of selected papers presented during the biannual meeting of the Classification and Data Analysis Group of SocietA Italiana di Statistica, which was held in Bologna, September 22-24, 2003. The scientific program of the conference included 80 contributed papers. the conference provided a large number of scientists and experts from home and abroad with an attractive forum for discussions and mutual exchange of knowledge. The talks in the different sessions focused on methodological developments in supervised and unsupervised classification and in data analysis, also p- viding relevant contributions in the context of applications. This suggested the presentation of the 43 selected papers in three parts as follows: CLASSIFICATION AND CLUSTERING Non parametric classification Clustering and dissimilarities MULTIVARIATE STATISTICS AND DATA ANALYSIS APPLIED MULTIVARIATE STATISTICS Environmental data Microarray data Behavioural and text data Financial data
Innovations in classification, data science, and information systems ; Proceedings of the 27th Annual Conference of the Gesellschaft für Klassifikation e.V., Brandenburg University of Technology, Cottbus, March 12-14, 2003
The volume presents innovations in data analysis and classification and gives an overview of the state of the art in these scientific fields and applications. Areas that receive considerable attention in the book are discrimination and clustering, data analysis and statistics, as well as applications in marketing, finance, and medicine. The reader will find material on recent technical and methodological developments and a large number of applications demonstrating the usefulness of the newly developed techniques.
Engineering Stochastic Local Search Algorithms. Designing, Implementing and Analyzing Effective Heuristics ; International Workshop, SLS 2007, Brussels, Belgium, September 6-8, 2007, Proceedings
Stochastic local search (SLS) algorithms enjoy great popularity as powerful and versatile tools for tackling computationally hard decision and optimization pr- lems from many areas of computer science, operations research, and engineering. However, in recent years it has become evident that at the core of this development task there is a highly complex engineering process, which combines various aspects of algorithm design with empirical analysis techniques and problem-specific background, and which relies heavily on knowledge from a number of disciplines and areas, including computer science, operations research, artificial intelligence, and statistics. This development process needs to be - sisted by a sound methodology that addresses the issues arising in the various phases of algorithm design, implementation, tuning, and experimental eval- tion.
Data Science and Classification
This volume provides new methodological developments in data analysis and classification. A wide range of topics is covered that includes the measurement of similarity and dissimilarity, methods for classification and clustering, network and graph analyses, analysis of symbolic data, and web mining. Apart from structural and theoretical results the book shows how to apply the proposed to a variety of problems, for example in medicine, microarray analysis, social network structures, and music. The combination of new methodological advances with the wide range of real applications collected in this volume is of special value for researchers when choosing the appropriate among newly developed analytical tools for their research problems in classification and data analysis.
COMPSTAT 2008 ; Proceedings in Computational Statistics
Presents methodological developments in Applied/Computational Statistics. This work covers a range of topics including Advances on Statistical Computing Environments, Methods for Classification and Clustering, Computation for Graphical Models and Bayes Nets, Computational Econometrics, and, Computational Statistics and Data Mining.
Analysis of phylogenetics and evolution with R
This book integrates a wide variety of data analysis methods into a single and flexible interface: the R language. This open source language is available for a wide range of computer systems and has been adopted as a computational environment by many authors of statistical software. Adopting R as a main tool for phylogenetic analyses will ease the workflow in biologists' data analyses, ensure greater scientific repeatability, and enhance the exchange of ideas and methodological developments.
