Books in the Handbook of Statistics series

Computational Analysis and Understanding of Natural Languages: Principles, Methods and Applications, Volume 38, the latest release in this monograph that provides a cohesive and integrated exposition of these advances and associated applications, includes new chapters on Linguistics: Core Concepts and Principles, Grammars, Open-Source Libraries, Application Frameworks, Workflow Systems, Mathematical Essentials, Probability, Inference and Prediction Methods, Random Processes, Bayesian Methods, Machine Learning, Artificial Neural Networks for Natural Language Processing, Information Retrieval, Language Core Tasks, Language Understanding Applications, and more. The synergistic confluence of linguistics, statistics, big data, and high-performance computing is the underlying force for the recent and dramatic advances in analyzing and understanding natural languages, hence making this series all the more important. Provides a thorough treatment of open-source libraries, application frameworks and workflow systems for natural language analysis and understandingPresents new chapters on Linguistics: Core Concepts and Principles, Grammars, Open-Source Libraries, Application Frameworks, Workflow Systems, Mathematical Essentials, Probability, and more

R is open source statistical computing software. Since the R core group was formed in 1997, R has been extended by a very large number of packages with extensive documentation along with examples freely available on the internet. It offers a large number of statistical and numerical methods and graphical tools and visualization of extraordinarily high quality. R was recently ranked in 14th place by the Transparent Language Popularity Index and 6th as a scripting language, after PHP, Python, and Perl. The book is designed so that it can be used right away bynovices while appealing to experienced users as well.Each article begins with a data example that can be downloaded directly from the R website. Data analysis questions are articulated following the presentation of the data. The necessary R commands are spelled out and executed and the output is presented and discussed. Other examples of data sets with a different flavor and different set of commands but following the theme of the article are presented as well. Eachchapter predents a hands-on-experience. R has superb graphical outlays and the book brings out the essentials in this arena. The end user can benefit immensely by applying the graphics to enhance research findings. The core statistical methodologies such as regression, survival analysis, and discrete data are all covered.

This volume focuses on theory and methods within the area of statistics. Topics covered include: a historical perspective; relations and identities; distributed function of statistics; extremes and asymptotics; and resampling methods.

Addresses emerging statistical challenges in epidemiological, biomedical, and pharmaceutical research. This volume features: methods for assessing Biomarkers, analysis of competing risks; clinical trials including sequential and group sequential, crossover designs, cluster randomized, and adaptive designs; and, structural equations modelling.

This volume aims to give an fresh overview on the subject of environmental statistics. Particular importance is placed on the formulation of relevant research, training, policy and regulation in academia, agencies and industries.

Describes how to develop Bayesian thinking, modelling and computation both from philosophical, methodological and application point of view. This book covers a range of topics including objective and subjective Bayesian inferences with a variety of applications in modelling categorical, survival, spatial, spatiotemporal, and more.

In order to make use of a diverse range of developments in the field, this volume addresses the need to review the different lines of researches and developments in stochastic processes. It presents a consolidated and comprehensive account for the benefit of students, researchers, and others.

Concerned with reviewing and unifying new ideas in the different lines of research and developments in stochastic processes of applied flavour, this volume consists of various topics in stochastic processes. Including manufacturing systems, random graphs and reliability.

Dealing primarily with applications of statistics, this text is divided into six parts; results for specific distributions; linear estimations; inferential methods; prediction; goodness-of-fit tests; and applications.

Hardbound. This volume is devoted to Sample Surveys, which is the most widely used method in statistical practice. It covers many theoretical and practical aspects of social and biological investigations, and is a valuable guide for those involved in designing sample surveys.