Mathematics

The statistical analysis of cost-effectiveness data is becoming increasingly important within health and medical research.

Disease mapping involves the analysis of geo-referenced disease incidence data and has many applications, for example within resource allocation, cluster alarm analysis, and ecological studies.

Cross-over trials are an important class of design used in the pharmaceutical industry and medical research, and their use continues to grow.

Over the last twenty years there has been a dramatic upsurge in the application of meta-analysis to medical research.

There has been substantial growth in the use of data monitoring committees in recent years, by both government agencies and the pharmaceutical industry.

* Includes five chapters that cover the basic principles of chemometrics analysis.

A practical guide to selecting and applying the most appropriate model for analysis of cross section data using EViews.

A practical guide to selecting and applying the most appropriate model for analysis of cross section data using EViews.

Visual attention is a relatively new area of study combining a number of disciplines: artificial neural networks, artificial intelligence, vision science and psychology.

Differential evolution is a very simple but very powerful stochastic optimizer.

Do you want to recognize the most suitable models for analysis of statistical data sets?

Image processing problems are often not well defined because real images are contaminated with noise and other uncertain factors.

Bayesian methods are a powerful tool in many areas of science and engineering, especially statistical physics, medical sciences, electrical engineering, and information sciences.

In this fully revised and expanded edition of Smooth Tests of Goodness of Fit, the latest powerful techniques for assessing statistical and probabilistic models using this proven class of procedures are presented in a practical and easily accessible manner.

"e;It is said if you take care of the pennies, the pounds will take care of themselves.

Claims reserving is central to the insurance industry.

Multivariable regression models are of fundamental importance in all areas of science in which empirical data must be analyzed.

Managing uncertainties in industrial systems is a daily challenge to ensure improved design, robust operation, accountable performance and responsive risk control.

Ecologists and environmental managers rely on mathematical models, both to understand ecological systems and to predict future system behavior.

A comprehensive, compilation and evaluation of the newest results in the field of enumerate evaluation of chromatographic data Aimed at the practicing professional, researchers and advanced students working in this area Special emphasis on practical applications While the principles of chromatography and multivariate mathematical-statistical methods are discussed separately, the book focuses on their interconnection.

Business intelligence is a broad category of applications and technologies for gathering, providing access to, and analyzing data for the purpose of helping enterprise users make better business decisions.

Graphical models are of increasing importance in applied statistics, and in particular in data mining.

This book is an introductory guide to using L vy processes for credit risk modelling.

Digital sound synthesis has long been approached using standard digital filtering techniques.

Handbook of Computational Econometrics examines the state of the art of computational econometrics and provides exemplary studies dealing with computational issues arising from a wide spectrum of econometric fields including such topics as bootstrapping, the evaluation of econometric software, and algorithms for control, optimization, and estimation.

The increasing cost of research means that scientists are in more urgent need of optimal design theory to increase the efficiency of parameter estimators and the statistical power of their tests.

Decision theory provides a formal framework for making logical choices in the face of uncertainty.

The increasing availability of data in our current, information overloaded society has led to the need for valid tools for its modelling and analysis.

This practical text is an essential source of information for those wanting to know how to deal with the variability that exists in every engineering situation.

Rare Event Simulation In a probabilistic model, a rare event is an event with a very small probability of occurrence.

Statistical and Methodological Aspects of Oral Health Research provides oral health researchers with an overview of the methodological aspects that are important in planning, conducting and analyzing their research projects whilst also providing biostatisticians with an idea of the statistical problems that arise when tackling oral health research questions.

Longitudinal surveys are surveys that involve collecting data from multiple subjects on multiple occasions.

Robust statistics is an extension of classical statistics that specifically takes into account the concept that the underlying models used to describe data are only approximate.

The field of high-throughput genetic experimentation is evolving rapidly, with the advent of new technologies and new venues for data mining.

Statistical methodology plays a key role in ensuring that DNA evidence is collected, interpreted, analyzed and presented correctly.

Spatial point processes are mathematical models used to describe and analyse the geometrical structure of patterns formed by objects that are irregularly or randomly distributed in one-, two- or three-dimensional space.

Complex mathematical and computational models are used in all areas of society and technology and yet model based science is increasingly contested or refuted, especially when models are applied to controversial themes in domains such as health, the environment or the economy.

This book offers a predominantly theoretical coverage of statistical prediction, with some potential applications discussed, when data and/ or parameters belong to a large or infinite dimensional space.

Heavy-tailed distributions are typical for phenomena in complex multi-component systems such as biometry, economics, ecological systems, sociology, web access statistics, internet traffic, biblio-metrics, finance and business.

Symbolic data analysis is a relatively new field that provides a range of methods for analyzing complex datasets.

R, an Open Source software, has become the de facto statistical computing environment.

"e;This well-written book provides a clear and accessible treatment of the theory of discrete and continuous-time Markov chains, with an emphasis towards applications.

ASSESSMENT METHODS IN STATISTICAL EDUCATION ASSESSMENT METHODS IN STATISTICAL EDUCATION AN INTERNATIONAL PERSPECTIVE Assessment Methods in Statistical Education: An International Perspective provides a modern, international perspective on assessing students of statistics in higher education.

Computational Colour Science Using MATLAB 2nd Edition offers a practical, problem-based approach to colour physics.

This text is an accessible, student-friendly introduction to the wide range of mathematical and statistical tools needed by the forensic scientist in the analysis, interpretation and presentation of experimental measurements.

Written by a teacher with many years' experience of teaching mathematics to primary school dyslexic and dyspraxic children with a wide range of abilities, this book is designed to be a practical teaching guide.

This important textbook provides an introduction to the concepts of the newly developed extended finite element method (XFEM) for fracture analysis of structures, as well as for other related engineering applications.

Text Mining: Applications and Theory presents the state-of-the-art algorithms for text mining from both the academic and industrial perspectives.

Complex multivariate testing problems are frequently encountered in many scientific disciplines, such as engineering, medicine and the social sciences.

High response rates have traditionally been considered as one of the main indicators of survey quality.