Probability and statistics

This book explores a range of prospective avenues, models, and operational and strategic approaches to Lean Six Sigma (LSS), a contemporary Continuous Improvement (CI) practice for achieving a quality-based competitive edge in organisations.

This book covers applications of machine learning in artificial intelligence.

This book features selected papers presented at the 2nd International Conference on Advanced Computing Technologies and Applications, held at SVKM's Dwarkadas J.

This book focuses on the latest developments in behaviormetrics and data science, covering a wide range of topics in data analysis and related areas of data science, including analysis of complex data, analysis of qualitative data, methods for high-dimensional data, dimensionality reduction, visualization of such data, multivariate statistical methods, analysis of asymmetric relational data, and various applications to real data.

This book is about how extreme and systemic risk can be analyzed in an integrated way.

This book explores key examples concerning the implementation of information technology and mathematical modeling to solve issues concerning environmental sustainability.

This book reconsiders statistical methods from the point of view of entropy, and introduces entropy-based approaches for data analysis.

This book occupies a unique position in the field of statistical analysis in the behavioural and social sciences in that it targets learners who would benefit from learning more conceptually and less computationally about statistical procedures and the software packages that can be used to implement them.

This book discusses significant research findings in the field of mathematical modelling, with particular emphasis on important applied-sciences, health, and social issues.

This book provides a contemporary treatment of quantitative economics, with a focus on data science.

This book presents the basic concepts of survival analysis and frailty models, covering both fundamental and advanced topics.

This book introduces systematically the application of Bayesian probabilistic approach in soil mechanics and geotechnical engineering.

This volume presents a collection of lecture notes of mini-courses taught at BICMR Summer School of Financial Mathematics, from May 29 to June 9, 2017.

This book presents recent developments in statistical methodologies with particular relevance to applications in forestry and environmental sciences.

Proposing the concept of real-world data circulation (RWDC), this book presents various practical and industry-related studies in human, mechanical, and social data domains.

This book focuses on the application of data mining techniques in cricket.

This book integrates the type-2 fuzzy sets and multiple criteria decision making analysis in recent years and offers an authoritative treatise on the essential topics, both at the theoretical and applied end.

This book presents and standardizes statistical models and methods that can be directly applied to both reliability and survival analysis.

This book explores various renewal processes in the context of probability theory, uncertainty theory and chance theory.

This book discusses the need to carefully and prudently apply various regression techniques in order to obtain the full benefits.

This book introduces a number of new sampling plans, such as time truncated life tests, skip sampling plans, resubmitted plans, mixed sampling plans, sampling plans based on the process capability index and plans for big data, which can be used for testing and inspecting products, from the raw-materials stage to the final product, in every industry using statistical process control techniques.

This book reconsiders statistical methods from the point of view of entropy, and introduces entropy-based approaches for data analysis.

This book explores a range of prospective avenues, models, and operational and strategic approaches to Lean Six Sigma (LSS), a contemporary Continuous Improvement (CI) practice for achieving a quality-based competitive edge in organisations.

This book aims to provide a comprehensive statistical picture of the Russian economic development covering the Imperial, Soviet, and New Russian periods.

This book presents the latest findings on network theory and agent-based modeling of economic and financial phenomena.

This book is a product of the Third International Conference on Computing, Mathematics and Statistics (iCMS2017) to be held in Langkawi in November 2017.

This book proposes, for the first time, a basic formulation for structural control that takes into account the stochastic dynamics induced by engineering excitations in the nature of non-stationary and non-Gaussian processes.

This is the first book that examines the diverse range of experimental methods currently being used in the social sciences, gathering contributions by working economists engaged in experimentation, as well as by a political scientist, psychologists and philosophers of the social sciences.

This book shows how to decompose high-dimensional microarrays into small subspaces (Small Matryoshkas, SMs), statistically analyze them, and perform cancer gene diagnosis.

This book presents a unified framework for the tractable analysis of large-scale, multi-antenna wireless networks using stochastic geometry.

 Deep Learning with R introduces deep learning and neural networks using the R programming language.

This introductory book offers a unique and unified overview of symplectic geometry, highlighting the differential properties of symplectic manifolds.

This monograph presents a modern treatment of (1) stochastic differential equations and (2) diffusion and jump-diffusion processes.

This book introduces readers to the financial markets, derivatives, structured products and how the products are modelled and implemented by practitioners.

This book first provides a review of various aspects of Bayesian statistics.

This book, specifically developed for students of psychology, covers a wide range of topics in statistics and research designs taught in psychology, in particular, and other disciplines like management, sociology, education, home science, and nutrition, in general, in most universities.

This book presents extensive information on structural health monitoring for suspension bridges.

This book discusses recent developments in mathematical programming and game theory, and the application of several mathematical models to problems in finance, games, economics and graph theory.

This book seeks to bridge the gap between statistics and computer science.

Recent applications of evolutionary game theory in the merging fields of the mathematical and social sciences are brilliantly portrayed in this book, which highlights social physics and shows how the approach can help to quantitatively model complex human-environmental-social systems.

The book presents theory and algorithms for secure networked inference in the presence of Byzantines.

This is an introductory text on a broad class of statistical estimators that are minimizers of convex functions.

This book presents various recently developed and traditional statistical techniques, which are increasingly being applied in social science research.

This textbook describes recent advances in genomics and bioinformatics and provides numerous examples of genome data analysis that illustrate its relevance to real world problems and will improve the reader's bioinformatics skills.

This book describes recent trends in growth curve modelling research in various subject areas, both theoretical and applied.

This book provides an accessible presentation of concepts from probability theory, statistical methods, the design of experiments and statistical quality control.

This book finds a broad domain of relevance in statistics and the social sciences.

This unique book addresses the statistical modelling and analysis of microbiome data using cutting-edge R software.

This book encompasses empirical evidences to understand the application of data analytical techniques in emerging contexts.

This book discusses systematic designs of stable adaptive fuzzy logic controllers employing hybridizations of Lyapunov strategy-based approaches/Hinfinity theory-based approaches and contemporary stochastic optimization techniques.