Stochastics

This book provides a versatile and lucid treatment of classic as well as modern probability theory, while integrating them with core topics in statistical theory and also some key tools in machine learning.

The book is based on both authors' several years of experience in teaching linear models at various levels.

This textbook reconstructs the statistics curriculum from the perspective of posterior probability.

Queueing network models have been widely applied as a powerful tool for modelling, performance evaluation, and prediction of discrete flow systems, such as computer systems, communication networks, production lines, and manufacturing systems.

This book provides a pedagogical examination of the way in which stochastic models are encountered in applied sciences and techniques such as physics, engineering, biology and genetics, economics and social sciences.

This textbook provides a straightforward, clear explanation of probability and random variables for communications engineering students.

A concise introduction covering all of the measure theory and probability most useful for statisticians.

The purpose of this book is to give a detailed account of some recent devel- ments in the ?

Over the past decade there has been an explosion of developments in mixed e?

This monograph offers a thorough and updated guide to the theory and methods of progressive censoring, an area that has experienced tremendous growth in recent years.

Despite advances in the field of geotechnical earthquake engineering, earthquakes continue to cause loss of life and property in one part of the world or another.

The book offers an introduction to the technical foundation of decentralized insurance models, for advanced undergraduate students, graduate students and practitioners.

This book developed out of my year-long course on asymptotic theory at Purdue University.

This book offers a comprehensive discussion of the Bayesian inference framework and demonstrates why this probabilistic approach is ideal for tackling the various modelling problems within quantitative finance.

Our object in writing this book is to present the main results of the modern theory of multivariate statistics to an audience of advanced students who would appreciate a concise and mathematically rigorous treatment of that material.

Introduces stochastic control and mathematical modelling to researchers and graduate students in applied mathematics, mathematical economics, and non-linear PDE theory.

Advanced Mathematical Tools for Automatic Control Engineers, Volume 2: Stochastic Techniques provides comprehensive discussions on statistical tools for control engineers.

This book provides an overview of the risk components of CoCo bonds.

This book contains the invited papers of the interdisciplinary workshop on "e;Stochastic Nonlinear Systems in Physics, Chemistry and Biology"e; held at the Center for Interdisciplinary Research (ZIF), University of Bielefeld, West Germany, October 5-11, 1980.

This book deals with certain important problems in Classical and Quantum Information Theory Quantum Information Theory, A Selection of Matrix Inequalities Stochastic Filtering Theory Applied to Electromagnetic Fields and Strings Wigner-distributions in Quantum Mechanics Quantization of Classical Field Theories Statistical Signal Processing Quantum Field Theory, Quantum Statistics, Gravity, Stochastic Fields and Information Problems in Information Theory It will be very helpful for students of Undergraduate and Postgraduate Courses in Electronics, Communication and Signal Processing.

The book covers all the basics of both the topics.

This book covers formulation, algorithms, and structural results of partially observed Markov decision processes, linking theory to real-world applications in controlled sensing.

This book provides a unique tour of university mathematics with the help of Python.

The aim of this book is to discuss various aspects associated with disseminating personal or business data collected in censuses or surveys or copied from administrative sources.

From the Preface by D.

Provides the mathematical, stochastic and graph theoretic methods to analyse the performance and robustness of complex networks and systems.

The focus of this book is the large-scale statistical behavior of solutions of divergence-form elliptic equations with random coefficients, which is closely related to the long-time asymptotics of reversible diffusions in random media and other basic models of statistical physics.

The subject of this book stands at the crossroads of ergodic theory and measurable dynamics.

Random Effect and Latent Variable Model Selection In recent years, there has been a dramatic increase in the collection of multivariate and correlated data in a wide variety of ?

A unique introduction to reproducing kernel Hilbert spaces, covering the fundamental underlying theory as well as a range of applications.

Starting with the Shannon-Wiener approach to mathematical information theory, allowing a mathematical "e;measurement"e; of an amount of information, the book begins by defining the terms message and information and axiomatically assigning an amount of information to a probability.

This book is devoted to real analysis methods for the problem of constructing Markov processes with boundary conditions in probability theory.

The general theory of stochastic processes and the more specialized theory of Markov processes evolved enormously in the second half of the last century.

Arbitrage Theory provides the foundation for the pricing of financial derivatives and has become indispensable in both financial theory and financial practice.

Expanding on the first edition of An Introduction to Continuous-Time Stochastic Processes, this concisely written book is a rigorous and self-contained introduction to the theory of continuous-time stochastic processes.

This book is composed of two texts, by R.

This book grew out of the Random Transformations and Invariance in Stochastic Dynamics conference held in Verona from the 25th to the 28th of March 2019 in honour of Sergio Albeverio.

This book develops the theory of continuous and discrete stochastic processes within the context of cell biology.

The subject of time series is of considerable interest, especiallyamong researchers in econometrics, engineering, and the naturalsciences.

This is the first comprehensive account of the theory of mass transportation problems and its applications.

This book systematically presents the topological structure of solution sets and attractability for nonlinear evolution inclusions, together with its relevant applications in control problems and partial differential equations.

In this text, modern applied mathematics and physical insight are used to construct the simplest and first nonlinear dynamical model for the Madden-Julian oscillation (MJO), i.

Decoupling theory provides a general framework for analyzing problems involving dependent random variables as if they were independent.

The second edition has not deviated significantly from the first.

Environmental Data Analysis with MatLab is a new edition that expands fundamentally on the original with an expanded tutorial approach, new crib sheets, and problem sets providing a clear learning path for students and researchers working to analyze real data sets in the environmental sciences.