"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.
In order to build a successful, Java-based application it is important to have a clear understanding of the principles underlying the various financial models.
Non-Gaussian distributions are the key theme of this book which addresses the causes and consequences of non-normality and time dependency in both asset returns and option prices.
The applications of image-based measurement are many and various: image-guided surgery, mobile-robot navigation, component alignment and photogrammetry, among others.
Most data sets collected by researchers are multivariate, and in the majority of cases the variables need to be examined simultaneously to get the most informative results.
A problem of broad interest - the estimation of the spectral gap for matrices or differential operators (Markov chains or diffusions) - is covered in this book.
Probabilistic Modelling in Bioinformatics and Medical Informatics has been written for researchers and students in statistics, machine learning, and the biological sciences.
Probabilistic Conditional Independence Structures provides the mathematical description of probabilistic conditional independence structures; the author uses non-graphical methods of their description, and takes an algebraic approach.
Safety critical and high-integrity systems, such as industrial plants and economic systems can be subject to abrupt changes - for instance due to component or interconnection failure, and sudden environment changes etc.
This book aims to present a state-of-the-art survey of theories and methods of reliability, maintenance, and warranty with emphasis on multi-unit systems, and to reflect current hot topics: imperfect maintenance, economic dependence, opportunistic maintenance, quasi-renewal processes, warranty with maintenance and economic dependency, and software testing and maintenance.
Many current texts in the area are just cookbooks and, as a result, students do not know why they perform the methods they are taught, or why the methods work.
Stochastic differential equations play an increasingly important role in modeling the dynamics of a large variety of systems in the natural sciences, and in technological applications.
Foresight in an engineering enterprise can make the difference between success and failure, and can be vital to the effective control of industrial systems.
It is said that six sigma methods are vital to survive, let alone thrive, in today's competitive markets, but what are these methods and how or when do we use them?
This guide offers a clear step-by-step approach for graduate students and early-career researchers, especially non-native English speakers, seeking to publish in international journals in the social sciences.
This book constitutes revised papers from the International Workshops held at the 22nd International Conference on Business Process Management, BPM 2024, in Krakow, Poland, during September 2024.
The authors of this book assert that Grid Square statistics, a method of aggregating data within a geographically defined Grid, may be an effective solution to approach geospatial data for big data integration.
The book presents a collection of peer-reviewed short papers selected from those presented at the International Conference Mathematical and Statistical Methods for Actuarial Sciences and Finance - MAF2024.
In this book, we explain the development of a new filtering method to estimate the hidden states of random variables for multiple non-stationary time series data.
This book develops robust design and assessment of product and production from viewpoint of system theory, which is quantized with the introduction of brand new concept of preferable probability and its assessment.
This fascinating book begins with fundamental definitions and notations of urn models before moving on to stochastic processes and applications of urn models in the field of finance.
This book of peer-reviewed short papers on methodological and applied statistics and demography is the third of four volumes from the 52nd Scientific Meeting of the Italian Statistical Society (SIS 2024), held in Bari, Italy, on June 17-20, 2024.
This book is interdisciplinary and unites several areas of applied probability, statistics, and computational mathematics including computer experiments, optimal experimental design, and global optimization.
This volume presents a comprehensive compilation of chapters whose topics were presented at the 2nd International Conference on Mathematical Analysis and Application in Modeling (CMAAM-2023), held at the Department of Mathematics & the Center for Mathematical Biology and Ecology, Jadavpur University, Kolkata, West Bengal, India, from 9-11 October 2023.
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 book presents peer-reviewed short papers on methodological and applied statistical research presented at the Italian Statistical Society’s international conference on “Statistics for Innovation”, SIS 2025, held in Genoa, Italy, June 16-18, 2025.
