Bøger i Contributions to Statistics serien

it deals with some hot topics in sampling theory, such as calibration, quantile-regression and multiple frame surveys and with innovative methodologies in important topics of both sampling theory and applications.

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.

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.

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.

This selection of articles emerged from different works presented "The Art of Semiparametrics" conference in 2003 in Berlin. Although each article represents an original contribution to its own field, all are written in a self-contained way that may be read by non-experts.

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.

Statisticians and experimentalists will find the latest trends in optimal experimental design research. Some papers are pioneering contributions, leading to new open research problems. It is a colection of peer reviewed papers.