From the reviews: "e;The huge literature in risk theory has been carefully selected and supplemented by personal contributions of the author, many of which appear here for the first time.
Author's Note: The material of this book has been reworked and expanded with a lot more detail and published in the author's 2014 book "e;Upper and Lower Bounds for Stochastic Processes"e; (Ergebnisse Vol.
To some extent, it would be accurate to summarize the contents of this book as an intolerably protracted description of what happens when either one raises a transition probability matrix P (i.
This 3-volume reference covers the entire field of epidemiology, from statistical methods and study design, to specialized areas such as molecular epidemiology, and applications in clinical medicine and health services research.
This book is the first comprehensive presentation of a central topic of stochastic geometry: random mosaics that are generated by Poisson processes of hyperplanes.
This book offers an easily accessible and comprehensive guide to the entire market research process, from asking market research questions to collecting and analyzing data by means of quantitative methods.
This treatise delves into the latest advancements in stochastic volatility models, highlighting the utilization of Markov chain Monte Carlo simulations for estimating model parameters and forecasting the volatility and quantiles of financial asset returns.
Unter dem Titel "Beschaffung, Lagerung, Absatz und Kosten des Einzelhandels" erschienen 1953,1956 und 1959 in den Schriften zur Handelsforschung (Band 1, 7 und 11) Dreijahresberichte (1949/51, 1952/54, 1955/57) über die Ergebnisse des vom Institut für Handelsforschung durch geführten Betriebsvergleichs des Einzelhandels in der Bundesrepublik Deutschland.
geschlossene Darstellung, welche die Plankostenrechnung in den Rahmen der kosten rechnerischen Entwicklung stellt und ihren Aufbau als ein in sich geschlossenes Sy stem wiedergibt.
This book introduces probabilistic modelling and explores its role in solving a broad spectrum of engineering problems that arise in Information Technology (IT).
This book presents a comprehensive series of methods in nonsmooth optimization, with a particular focus on their application in stochastic programming and dedicated algorithms for decision-making under uncertainty.
This edited volume on machine learning and big data analytics (Proceedings of ICDSAI 2023), that was held on April 24-25, 2023 by CSUSB USA, International Association of Academicians (IAASSE), and Lendi Institute of Engineering and Technology, Vizianagaram, India is intended to be used as a reference book for researchers and practitioners in the disciplines of AI and Data Science.
This book presents a unique collection of contributions on modern methods and applications in three key areas of statistics, celebrating the significant work of Wolfgang Schmid in this field.
This book offers a novel multi-portfolio approach and stochastic programming formulations for modeling and solving contemporary supply chain risk management problems.
This book explores the independence of official statistics and describes the various legal and professional norms, institutional arrangements, instruments and practices that statisticians have developed over recent decades to protect their work from political interference.
This textbook provides a comprehensive exploration of anomalous stochastic processes and extreme events, commonly referred to as "e;black swans,"e; with a particular focus on (multi-)fractal approaches and continuous-time random walks.
Multi-state System Reliability Analysis and Optimization for Engineers and Industrial Managers presents a comprehensive, up-to-date description of multi-state system (MSS) reliability as a natural extension of classical binary-state reliability.
Biological and biomedical studies have entered a new era over the past two decades thanks to the wide use of mathematical models and computational approaches.
Bayesian Inference for Probabilistic Risk Assessment provides a Bayesian foundation for framing probabilistic problems and performing inference on these problems.
A recent development in SDC-related problems is the establishment of intelligent SDC models and the intensive use of LMI-based convex optimization methods.
Regression is the branch of Statistics in which a dependent variable of interest is modelled as a linear combination of one or more predictor variables, together with a random error.
"e;Optimal Observation for Cyber-physical Systems"e; addresses the challenge, fundamental to the design of wireless sensor networks (WSNs), presented by the obligatory trade-off between precise estimates and system constraints.
Information theory has proved to be effective for solving many computer vision and pattern recognition (CVPR) problems (such as image matching, clustering and segmentation, saliency detection, feature selection, optimal classifier design and many others).
"e;Failure Rate Modeling for Reliability and Risk"e; focuses on reliability theory, and to the failure rate (hazard rate, force of mortality) modeling and its generalizations to systems operating in a random environment and to repairable systems.
Aimed primarily at graduate students and researchers, this text is a comprehensive course in modern probability theory and its measure-theoretical foundations.
Stochastic control is one of the methods being used to find optimal decision-making strategies in fields such as operations research and mathematical finance.
Identification of Continuous-time Models from Sampled Data presents an up-to-date view of this active area of research, describing recent methods and software tools and offering new results in areas such as: time and frequency domain optimal statistical approaches to identification; parametric identification for linear, nonlinear and stochastic systems; identification using instrumental variable, subspace and data compression methods; closed-loop and robust identification; and continuous-time modeling from non-uniformly sampled data and for systems with delay.
