Bücher der Reihe Contributions to Statistics

The coverage of the material falls squarely into the following categories: (a) Survival analysis and multivariate survival analysis, (b) Time series and longitudinal data analysis, (c) Statistical model development and (d) Applied statistical modelling.

This volume contains pioneering contributions to both the theory and practice of optimal experimental design. Topics include the optimality of designs in linear and nonlinear models, as well as designs for correlated observations and for sequential experimentation.

This volume, which highlights recent advances in statistical methodology and applications, is divided into two main parts. The first part presents theoretical results on estimation techniques in functional statistics, while the second examines three key areas of application: estimation problems in queuing theory, an application in signal processing, and the copula approach to epidemiologic modelling.The book¿s peer-reviewed contributions are based on papers originally presented at the Marrakesh International Conference on Probability and Statistics held in December 2013.

The use of computational methods in statistics to face complex problems and highly dimensional data, as well as the widespread availability of computer technology, is no news.

The book is addressed to statisticians working at the forefront of the statistical analysis of complex and high dimensional data and offers a wide variety of statistical models, computer intensive methods and applications: network inference from the analysis of high dimensional data;

One of the main applications of statistical smoothing techniques is nonparametric regression. Smoothing techniques in regression as well as other statistical methods are increasingly applied in biosciences and economics. Introduced are new developments in scatterplot smoothing and applications in statistical modelling.

Devoted to the growing impact of statistical methodology and statistical computing in industry the aim of this book is to link the three components: Statistics - industry - computers. pharma - statistics; This book concentrates on the interface between statistical needs in industry and statistical methods developed by statisticians and engineers.

This volume is the proceedings of the 4th International Workshop on Model-Oriented Data Analysis. The editors are also grateful to Intracom (Greece), the Ionian Bank and the Procter & Gamble Company (USA) for their generous support.

The coverage of the material falls squarely into the following categories: (a) Survival analysis and multivariate survival analysis, (b) Time series and longitudinal data analysis, (c) Statistical model development and (d) Applied statistical modelling.

Diverse driving forces, processes and actors are responsible for different trends in the development of megacities and large urban areas. Under the dynamics of global change, megacities are themselves changing: On the one hand they are prone to increasing socio-economic vulnerability due to pronounced poverty, socio-spatial and political fragmentation, sometimes with extreme forms of segregation, disparities and conflicts. On the other hand megacities offer positive potential for global transformation, e.g. minimisation of space consumption, highly effective use of resources, efficient disaster prevention and health care options ¿ if good strategies were developed.  At present in many megacities and urban areas of the developing world and the emerging economies the quality of life is eroding. Most of the megacities have grown to unprecedented size, and the pace of urbanisation has far exceeded the growth of the necessary infrastructure and services. As a result, an increasing number of urban dwellers are left without access to basic amenities like clean drinking water, fresh air and safe food. Additionally, social inequalities lead to subsequent and significant intra-urban health inequalities and unbalanced disease burdens that can trigger conflict and violence between subpopulations. The guiding idea of our book lies in a multi- and interdisciplinary approach to the complex topic of megacities and urban health that can only be adequately understood when different disciplines share their knowledge and methodological tools to work together. We hope that the book will allow readersto deepen their understanding of the complex dynamics of urban and megacity populations through the lens of public health, geographical and other research perspectives.

The failure of standard multivariate statistics to analyze such functional data has led the statistical community to develop appropriate statistical methodologies, called Functional Data Analysis (FDA).

This book presents a collection of statistical methods and procedures to assess data coming from educational systems.

The book presents statistical methods and models that can usefully support the ev- uation of educational services and quality of products. The contributions collected in this book summarize the work of several researchers from the universities of Bologna, Firenze, Napoli and Padova. The contributions are written with a cons- tent notation and a uni?ed view, and concern methodological advances developed mostly with reference to speci?c problems of evaluation using real data sets. The evaluation of educational services, as well as the analysis of judgements and preferences, poses severe methodological challenges because of the presence of one or more of the following aspects: the observational (non experimental) nature of the context, which is associated with the well-known problems of selection bias and presence of nuisance factors; the hierarchical structure of the data, that entails c- related observations and consideration of effects at different levels of the hierarchy and their interactions (multilevel analysis); the multivariate and qualitative nature of the dependent variable, that requires the use of ad hoc statistical methodologies; the presence of non observable factors, e. g. the satisfaction, calling for the use of latent variables models; the simultaneous presence of components of pleasure and components of uncertainty in the explication of the judgments, that asks for the speci?cation and estimation of mixture models. The ?rst part of the book deals with latent variable models.

Its theory and practice have since become important in many scientific and technological fields, ranging from optimal designs for dynamic models in pharmacological research, to designs for industrial experimentation, to designs for simulation experiments in environmental risk management, to name but a few.

Regression and state space models with time varying coefficients are treated in a thorough manner. Additionally, methods are developed to test for the constancy of regression coefficients in situations where one knows already that some coefficients follow a random walk, thereby one is enabled to find out which of the coefficients varies over time.

The use of computational methods in statistics to face complex problems and highly dimensional data, as well as the widespread availability of computer technology, is no news.

This book covers methods for spatial statistical analysis suitable for modeling spatial information in support of decision systems. Includes data mining, point processes analysis, nearest neighbor statistics and cluster detection, Fuzzy Regression and more.

This volume contains complete texts of a series of lectures presented at a summer school on the subject, held at Charles University, Prague, in July 1991. The contributors cover the problems of change point detection, stochastic approximation, multiple hypotheses testing and many other topics.

Thus, Total Quality refers to the global capacity of a company to fit its system to the real needs of its customers by designing products which are able to match the customers' taste and by implementing a statistical control of both the product and the Customer Satisfaction.

Reduced rank regression is widely used in statistics to model multivariate data. In this monograph, theoretical and data analytical approaches are developed for the application of reduced rank regression in multivariate prediction problems.

In particular up-to-date-information is presented in detection of systematic changes, in series of observation, in robust regression analysis, in numerical empirical processes and in related areas of actuarial sciences.

Diverse driving forces, processes and actors are responsible for different trends in the development of megacities and large urban areas. This book allows readers to deepen their understanding of the complex dynamics of urban and megacity populations through the lens of public health, geographical and other research perspectives.

The failure of standard multivariate statistics to analyze such functional data has led the statistical community to develop appropriate statistical methodologies, called Functional Data Analysis (FDA).

This book collects several contributions, written both by statisticians and medical doctors, which focus on the identification of new diagnostic, therapeutic and organizational strategies in order to improve the occurrence of clinical outcomes for Acute Coronary Syndromes (ACS) patients.

This book covers methods for spatial statistical analysis suitable for modeling spatial information in support of decision systems. Includes data mining, point processes analysis, nearest neighbor statistics and cluster detection, Fuzzy Regression and more.

The numerous applications (micro-arrays, paleo- ecological data, radar waveforms, spectrometric curves, speech recognition, continuous time series, 3-D images, etc.) in various fields (biology, econometrics, environmetrics, the food industry, medical sciences, paper industry, etc.) make researching this statistical topic very worthwhile.

This book presents a collection of statistical methods and procedures to assess data coming from educational systems.

This intellectually stimulating atmosphere is achieved by limiting the number of participants to around eighty, by the choice of location so that participants can live as a community, and, of course, through the care ful selection of scientific direction made by the Programme Committee.

This volume contains a substantial number of the papers presented at the mODa 7 conference. mODastands for Model Oriented Data Analysis and pre­ vious conferences have been held in Wartburg (1987) (then in the GDR), St Kirik monastery, Bulgaria (1990), Petrodvorets, St Petersburg, Russia (1992), The island of Spetsos, Greece (1995), the Centre International de Rencontres Mathematiques, Marseilles, France (1998) and Puchberg/Schneeberg, Aus­ tria, (2001). The purpose of these workshops has traditionally been to bring together scientists from the East and West interested in the optimal design of exper­ iments and related topics and younger and senior researchers in the field. These traditions remain vital to the health of the series. During this period Europe has seen increasing unity and the organizers of and participants in mODa must take some satisfaction from the fact that the youthful ideals of the founders of the series are reflected in this transition. The present conference and mODa 6 are supported by a European Union conference grant (contract HPCF-CT 2000 00045) whose funding emphasis is on younger participants. The company GlaxoSmithKline has very generously continued its support. We are very grateful for these substantial contribu­ tions.

The numerous applications (micro-arrays, paleo- ecological data, radar waveforms, spectrometric curves, speech recognition, continuous time series, 3-D images, etc.) in various fields (biology, econometrics, environmetrics, the food industry, medical sciences, paper industry, etc.) make researching this statistical topic very worthwhile.