Mathematics

Data mining is the process of automatically searching large volumes of data for models and patterns using computational techniques from statistics, machine learning and information theory; it is the ideal tool for such an extraction of knowledge.

Cluster analysis comprises a range of methods for classifying multivariate data into subgroups.

In 1989 the first edition of this book set out Gittins' pioneering index solution to the multi-armed bandit problem and his subsequent investigation of a wide of sequential resource allocation and stochastic scheduling problems.

A thorough introduction to the fundamentals of probability theory This book offers a detailed explanation of the basic models and mathematical principles used in applying probability theory to practical problems.

A thorough introduction to the fundamentals of probability theory This book offers a detailed explanation of the basic models and mathematical principles used in applying probability theory to practical problems.

In the spatial or spatio-temporal context, specifying the correct covariance function is fundamental to obtain efficient predictions, and to understand the underlying physical process of interest.

This book provides a comprehensive introduction to actuarial mathematics, covering both deterministic and stochastic models of life contingencies, as well as more advanced topics such as risk theory, credibility theory and multi-state models.

This book provides a comprehensive introduction to actuarial mathematics, covering both deterministic and stochastic models of life contingencies, as well as more advanced topics such as risk theory, credibility theory and multi-state models.

Cluster analysis comprises a range of methods for classifying multivariate data into subgroups.

A guide to the validation and risk management of quantitative models used for pricing and hedging Whereas the majority of quantitative finance books focus on mathematics and risk management books focus on regulatory aspects, this book addresses the elements missed by this literature--the risks of the models themselves.

Bayesian analysis of complex models based on stochastic processes has in recent years become a growing area.

Stochastic processes are widely used for model building in the social, physical, engineering and life sciences as well as in financial economics.

Most books in reliability theory are dealing with a description of component and system states as binary: functioning or failed.

Most books in reliability theory are dealing with a description of component and system states as binary: functioning or failed.

Few books on statistical data analysis in the natural sciences are written at a level that a non-statistician will easily understand.

Queueing analysis is a vital tool used in the evaluation of system performance.

Bayesian Networks, the result of the convergence of artificial intelligence with statistics, are growing in popularity.

Throughout the social, medical and other sciences the importance of understanding complex hierarchical data structures is well understood.

Fuzzy Multicriteria Decision-Making: Models, Algorithms and Applications addresses theoretical and practical gaps in considering uncertainty and multicriteria factors encountered in the design, planning, and control of complex systems.

In the spatial or spatio-temporal context, specifying the correct covariance function is fundamental to obtain efficient predictions, and to understand the underlying physical process of interest.

Statistical data are not always precise numbers, or vectors, or categories.

Statistical data are not always precise numbers, or vectors, or categories.

This is the first book-length treatment of statistical surveillance methods used in financial analysis.

A simple and systematic guide to the planning and performance of investigations concerned with health and disease and with health care Offers researchers help in choosing a topic and to think about shaping objectives and ideas and to link these with the appropriate choice of method Fully updated with new sections on the use of the Web and computer programmes freely available in the planning, performance or analysis of studies

This book provides a thorough analysis of internal rating systems.

Models and methods for operational risks assessment and mitigation are gaining importance in financial institutions, healthcare organizations, industry, businesses and organisations in general.

Biplots are a graphical method for simultaneously displaying two kinds of information; typically, the variables and sample units described by a multivariate data matrix or the items labelling the rows and columns of a two-way table.

An insightful, hands-on focus on the statistical methods used by compensation and human resources professionals in their everyday work Across various industries, compensation professionals work to organize and analyze aspects of employment that deal with elements of pay, such as deciding base salary, bonus, and commission provided by an employer to its employees for work performed.

This book grew out of an online interactive offered through statcourse.

An in-depth guide to understanding probability distributions and financial modeling for the purposes of investment management In Financial Models with L vy Processes and Volatility Clustering, the expert author team provides a framework to model the behavior of stock returns in both a univariate and a multivariate setting, providing you with practical applications to option pricing and portfolio management.

An in-depth guide to understanding probability distributions and financial modeling for the purposes of investment management In Financial Models with L vy Processes and Volatility Clustering, the expert author team provides a framework to model the behavior of stock returns in both a univariate and a multivariate setting, providing you with practical applications to option pricing and portfolio management.

Most existing books on wavelets are either too mathematical or they focus on too narrow a specialty.

Most existing books on wavelets are either too mathematical or they focus on too narrow a specialty.

Praise for the First Edition "e; .

A comprehensive look at how probability and statistics is applied to the investment process Finance has become increasingly more quantitative, drawing on techniques in probability and statistics that many finance practitioners have not had exposure to before.

A comprehensive look at how probability and statistics is applied to the investment process Finance has become increasingly more quantitative, drawing on techniques in probability and statistics that many finance practitioners have not had exposure to before.

Mathematics of Bioinformatics: Theory, Methods, and Applications provides a comprehensive format for connecting and integrating information derived from mathematical methods and applying it to the understanding of biological sequences, structures, and networks.

A practical, one-stop reference on the theory and applications of statistical data editing and imputation techniques Collected survey data are vulnerable to error.

This book represents the most comprehensive and up-to-date collection of information on the topic of computational molecular biology.

Combining theoretical, methodological, and practical aspects, Latent Class Analysis of Survey Error successfully guides readers through the accurate interpretation of survey results for quality evaluation and improvement.

A comprehensive, one-stop guide to identifying, reducing, and managing nonresponse in household surveys Nonresponse and its impact on the sample selection mechanism of a survey is a common problem that often arises while collecting survey data.

A guide to modeling analyses for financial and sports gambling markets, with a focus on major current events Addressing the highly competitive and risky environments of current-day financial and sports gambling markets, Forecasting in Financial and Sports Gambling Markets details the dynamic process of constructing effective forecasting rules based on both graphical patterns and adaptive drift modeling (ADM) of cointegrated time series.

A comprehensive treatment on the use of quantitative modeling for decision making and best practices in the service industries Making up a significant part of the world economy, the service sector is a rapidly evolving field that is relied on to dictate the public's satisfaction and success in various areas of everyday life, from banking and communications to education and healthcare.

An essential, up-to-date guide to the design of studies and selection of the correct QoL instruments for observational studies and clinical trials.

Groundwater is a vital source of water throughout the world.

Many ecological phenomena may be modelled using apparently random processes involving space (and possibly time).

Sensitivity analysis should be considered a pre-requisite for statistical model building in any scientific discipline where modelling takes place.

The need to understand, interpret and analyse competing risk data is key to many areas of science, particularly medical research.

Publication bias is the tendency to decide to publish a study based on the results of the study, rather than on the basis of its theoretical or methodological quality.

There have been many advances in the theory and applications of discrete distributions in recent years.