This book introduces the Learning-Augmented Network Optimization (LANO) paradigm, which interconnects network optimization with the emerging AI theory and algorithms and has been receiving a growing attention in network research.
This book provides a thorough understanding of distribution theory and data analysis using statistical software to solve problems related to basic statistics, probability models, and simulation.
This book discusses the theory and practice of teaching biostatistics to students in the life sciences, in particular medical and dental trainees and researchers, as well as its crucial importance to biomedical research and evidence-based health care.
This book introduces the fundamentals of the technology satisfaction model (TSM), supporting readers in applying the Rasch model and structural equation modeling (SEM) - a multivariate technique - to higher education (HE) research.
This proceedings volume features top contributions in modern statistical methods from Statistics 2021 Canada, the 6th Annual Canadian Conference in Applied Statistics, held virtually on July 15-18, 2021.
Using a novel integration of mathematics and Python codes, this book illustrates the fundamental concepts that link probability, statistics, and machine learning, so that the reader can not only employ statistical and machine learning models using modern Python modules, but also understand their relative strengths and weaknesses.
This book provides a blend of quantitative and qualitative approaches to decision making, while also bridging the gap between the theory of how to make good decisions versus how people actually make decisions.
Dieses Lehrbuch vermittelt Methoden der Datenanalytik zur Abbildung der Technischen Zuverlässigkeit und Risikoprognose unter Zuhilfenahme der Probabilistik, Statistik sowie der Modellbildung.
This textbook provides basic quantitative models allowing researchers and decision makers to a) assess viability of threatened populations and evaluate the success of species reintroductions, b) estimate invasion abilities of alien species, c) evaluate the persistence of metapopulations subjected to habitat destruction and fragmentation, d) analyze policies and strategies for the sustainable harvesting of biological resources, and e) assess the course of human and nonhuman diseases and the possible containment measures.
This book aims to predict the Mathematical Foundations of Statistical Mechanics and explain the measurable properties of macroscopic systems on the basis of the properties and behaviour of the microscopic constituents of those systems.
This book offers an overview on the main modern important topics in random variables, random processes, and decision theory for solving real-world problems.
This book constitutes the refereed proceedings of the First International Conference on Analytical and Computational Methods in Probability Theory and its Applications, ACMPT 2017, held in Moscow, Russia, in October 2017.
This is the first comprehensive book on Trotter-Kato approximations of stochastic differential equations (SDEs) in infinite dimensions and applications.
This book introduces and discusses the most important aspects of clinical research methods and biostatistics for oncologists, pursuing a tailor-made and practical approach.
This book introduces Probability Theory with R software and explains abstract concepts in a simple and easy-to-understand way by combining theory and computation.
In an era dominated by mathematical and statistical models, this book unravels the profound significance of these tools in decoding uncertainties within numerical, observational, and calculation-based data.
Partial least squares (PLS) regression is, at its historical core, a black-box algorithmic method for dimension reduction and prediction based on an underlying linear relationship between a possibly vector-valued response and a number of predictors.
This book helps quench the quest of knowledge of academicians, researchers, and others interested in developing a complete and critical understanding of consumer happiness.
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.
This book, written by two mathematicians from the University of Southern California, provides a broad introduction to the important subject of nonlinear mixture models from a Bayesian perspective.
This book seeks new perspectives on the growing inequalities that our societies face, putting forward Structured Additive Distributional Regression as a means of statistical analysis that circumvents the common problem of analytical reduction to simple point estimators.
This book is a short, but complete, introduction to the Loewner equation and the SLEs, which are a family of random fractal curves, as well as the relevant background in probability and complex analysis.
Item response theory (IRT) is widely used in education and psychology and is expanding its applications to other social science areas, medical research, and business as well.
A revelatory tale of how the human brain develops, from conception to birth and beyondBy the time a baby is born, its brain is equipped with billions of intricately crafted neurons wired together through trillions of interconnections to form a compact and breathtakingly efficient supercomputer.
Full of real-world case studies and practical advice, Exploratory Multivariate Analysis by Example Using R, Second Edition focuses on four fundamental methods of multivariate exploratory data analysis that are most suitable for applications.
Growth curve models in longitudinal studies are widely used to model population size, body height, biomass, fungal growth, and other variables in the biological sciences, but these statistical methods for modeling growth curves and analyzing longitudinal data also extend to general statistics, economics, public health, demographics, epidemiology, SQC, sociology, nano-biotechnology, fluid mechanics, and other applied areas.
Accessible to a variety of readers, this book is of interest to specialists, graduate students and researchers in mathematics, optimization, computer science, operations research, management science, engineering and other applied areas interested in solving optimization problems.
This book provides, as simply as possible, sound foundations for an in-depth understanding of reliability engineering with regard to qualitative analysis, modelling, and probabilistic calculations of safety and production systems.
