The first book to examine weakly stationary random fields and their connections with invariant subspaces (an area associated with functional analysis).
This monograph provides a self-contained and easy-to-read introduction to non-commutative multiple-valued logic algebras; a subject which has attracted much interest in the past few years because of its impact on information science, artificial intelligence and other subjects.
'A statistical national treasure' Jeremy Vine, BBC Radio 2'Required reading for all politicians, journalists, medics and anyone who tries to influence people (or is influenced) by statistics.
Computational finance is increasingly important in the financial industry, as a necessary instrument for applying theoretical models to real-world challenges.
For a solid foundation of important statistical methods, the concise, single-source text unites linear regression with analysis of experiments and provides students with the practical understanding needed to apply theory in real data analysis problems.
Drawing upon a wealth of past research and results, this book provides a comprehensive summary of state-of-the-art methods for empirical modeling of forest trees and stands.
This book provides a comprehensive methodology to measure systemic risk in many of its facets and dimensions based on state-of-the-art risk assessment methods.
This book constitutes the refereed proceedings of the 12th International Conference on Language and Automata Theory and Applications, LATA 2018, held in Ramat Gan, Israel, in April 2018.
This book introduces both conceptual and procedural aspects of cutting-edge data science methods, such as dynamic data visualization, artificial neural networks, ensemble methods, and text mining.
Limit theorems for random sequences may conventionally be divided into two large parts, one of them dealing with convergence of distributions (weak limit theorems) and the other, with almost sure convergence, that is to say, with asymptotic prop- erties of almost all sample paths of the sequences involved (strong limit theorems).
Large Covariance and Autocovariance Matrices brings together a collection of recent results on sample covariance and autocovariance matrices in high-dimensional models and novel ideas on how to use them for statistical inference in one or more high-dimensional time series models.
Item Response Theory clearly describes the most recently developed IRT models and furnishes detailed explanations of algorithms that can be used to estimate the item or ability parameters under various IRT models.
Introduction to the Theory of Optimization in Euclidean Space is intended to provide students with a robust introduction to optimization in Euclidean space, demonstrating the theoretical aspects of the subject whilst also providing clear proofs and applications.
This book provides clear instructions to researchers on how to apply Structural Equation Models (SEMs) for analyzing the inter relationships between observed and latent variables.
This introduction to visualization techniques and statistical models for second language research focuses on three types of data (continuous, binary, and scalar), helping readers to understand regression models fully and to apply them in their work.
In this book the authors have assembled the "e;best techniques from a great variety of sources, establishing a benchmark for the field of statistical computing.
Probability theory and its applications represent a discipline of fun- damental importance to nearly all people working in the high-tech- nology world that surrounds us.
Intelligent Modeling, Prediction, and Diagnosis from Epidemiological Data: COVID-19 and Beyond is a handy treatise to elicit and elaborate possible intelligent mechanisms for modeling, prediction, diagnosis, and early detection of diseases arising from outbreaks of different epidemics with special reference to COVID-19.
This book offers comprehensive information on the theory, models and algorithms involved in state-of-the-art multivariate time series analysis and highlights several of the latest research advances in climate and environmental science.
This book offers a comprehensive reference guide to neutrosophic theory and its applications in decision-making in numerous disciplines, ranging from business, economics and management, computer science, health and environmental sciences, and many others.
