Probability and statistics

This book introduces the latest research on advanced control charts and new machine learning approaches to detect abnormalities in the smart manufacturing process.

Dedicated to one of the most outstanding researchers in the field of statistics, this volume in honor of C.

This book deals with selected problems of machine perception, using various 2D and 3D imaging sensors.

This collection honours Ron Doney's work and includes invited articles by his collaborators and friends.

Highlighting the latest advances in stochastic analysis and its applications, this volume collects carefully selected and peer-reviewed papers from the 5th International Conference on Stochastic Methods (ICSM-5), held in Moscow, Russia, November 23-27, 2020.

A coherent, concise, and comprehensive course in the statistics needed for a modern career in chemical engineering covers all of the concepts required for the American Fundamentals of Engineering Examination.

Quantile regression is an approach to data at a loss of homogeneity, for example (1) data with outliers, (2) skewed data like corona - deaths data, (3) data with inconstant variability, (4) big data.

These lecture notes provide a rapid, accessible introduction to Bayesian statistical methods.

This textbook and guide focuses on methodologies for bias analysis in epidemiology and public health, not only providing updates to the first edition but also further developing methods and adding new advanced methods.

A common question posed to PhD students from friends and family is, "e;What will you do after?

This book provides an in-depth account of modern methods used to bound the supremum of stochastic processes.

This is the first book to systematically present control theory for stochastic distributed parameter systems, a comparatively new branch of mathematical control theory.

This book provides a concise introduction to exponential families.

This book provides a practical guide to the analysis of data from randomized controlled trials (RCT).

Fuzzy cognitive maps (FCMs) have gained popularity in the scientific community due to their capabilities in modeling and decision making for complex problems.

The spectral geometry of infinite graphs deals with three major themes and their interplay: the spectral theory of the Laplacian, the geometry of the underlying graph, and the heat flow with its probabilistic aspects.

This book presents a general method for deriving higher-order statistics of multivariate distributions with simple algorithms that allow for actual calculations.

This book provides a unified exposition of some fundamental theoretical problems in high-dimensional statistics.

The intention of this collection agrees with the purposes of the homonymous mini-symposium (MS) at ICIAM-2019, which were to overview the essentials of geometric calculus (GC) formalism, to report on state-of-the-art applications showcasing its advantages and to explore the bearing of GC in novel approaches to deep learning.

This textbook is the result of the enhancement of several courses on non-equilibrium statistics, stochastic processes, stochastic differential equations, anomalous diffusion and disorder.

This textbook tackles the problem of formulating AI systems by combining probabilistic modeling and deep learning.

The nonequilibrium behavior of nanoscopic and biological systems, which are typically strongly fluctuating, is a major focus of current research.

This book provides a guided approach to the geostatistical modelling of compositional spatial data.

This book introduces readers to Bayesian optimization, highlighting advances in the field and showcasing its successful applications to computer experiments.

The stability analysis of stochastic models for telecommunication systems is an intensively studied topic.

This book is devoted to the development of optimal control theory for finite dimensional systems governed by deterministic and stochastic differential equations driven by vector measures.

This textbook offers a comprehensive introduction to Machine Learning techniques and algorithms.

This book discusses a link between statistical theory and quantum theory based on the concept of epistemic processes.

This textbook teaches some of the basic econometric methods and the underlying assumptions behind them.

This book presents covariance matrix estimation and related aspects of random matrix theory.

This book presents an introduction to variational analysis, a field which unifies theories and techniques developed in calculus of variations, optimization, and control, and covers convex analysis, nonsmooth analysis, and set-valued analysis.

This volume highlights recent advances in data science, including image processing and enhancement on large data, shape analysis and geometry processing in 2D/3D, exploration and understanding of neural networks, and extensions to atypical data types such as social and biological signals.

This book focuses on important decision points and evidence needed for making decisions at these points during the development of a new drug.

This book discusses supply chain management, focusing on developments within modelling the dynamic behaviour of the supply chain.

The cooperation and contamination between mathematicians, statisticians and econometricians working in actuarial sciences and finance is improving the research on these topics and producing numerous meaningful scientific results.

This textbook offers an approachable introduction to stochastic processes that explores the four pillars of random walk, branching processes, Brownian motion, and martingales.

This textbook introduces the use of Python programming for exploring and modelling data in the field of Earth Sciences.

This book presents techniques for determining uncertainties in numerical solutions with applications in the fields of business administration, civil engineering, and economics, using Excel as a computational tool.

This book constitutes the refereed proceedings of the 19th International Conference on Artificial Intelligence in Medicine, AIME 2021, held as a virtual event, in June 2021.

This book studies values and attitudes in the Gulf region.

This book explores the analysis of social phenomena, using a multidisciplinary approach while addressing statistical, economic, sociological, as well as psychological issues.

This book presents state-of-the-art solution methods and applications of stochastic optimal control.

The main focus of this book is on presenting advances in fuzzy statistics, and on proposing a methodology for testing hypotheses in the fuzzy environment based on the estimation of fuzzy confidence intervals, a context in which not only the data but also the hypotheses are considered to be fuzzy.

This book presents the state-of-the-art methodology and detailed analytical models and methods used to assess the reliability of complex systems and related applications in statistical reliability engineering.

Modelling trends and cycles in economic time series has a long history, with the use of linear trends and moving averages forming the basic tool kit of economists until the 1970s.

This book focuses on important decision points and evidence needed for making decisions at these points during the development of a new drug.

This book develops survey data analysis tools in Python, to create and analyze cross-tab tables and data visuals, weight data, perform hypothesis tests, and handle special survey questions such as Check-all-that-Apply.

Bayesian Inference of State Space Models: Kalman Filtering and Beyond offers a comprehensive introduction to Bayesian estimation and forecasting for state space models.

The adoption of multilayer analysis techniques is rapidly expanding across all areas of knowledge, from social sciences (the first facing the complexity of such structures, decades ago) to computer science, from biology to engineering.

This book presents the latest findings on statistical inference in multivariate, multilinear and mixed linear models, providing a holistic presentation of the subject.