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Books in Probability theory and stochastic processes

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Fundamentals of Advanced Mathematics V2

  • 1st Edition
  • January 17, 2018
  • Henri Bourles
  • English
  • Hardback
    9 7 8 - 1 - 7 8 5 4 8 - 2 4 9 - 6
  • eBook
    9 7 8 - 0 - 0 8 - 1 0 2 3 8 5 - 3
The three volumes of this series of books, of which this is the second, put forward the mathematical elements that make up the foundations of a number of contemporary scientific methods: modern theory on systems, physics and engineering. Whereas the first volume focused on the formal conditions for systems of linear equations (in particular of linear differential equations) to have solutions, this book presents the approaches to finding solutions to polynomial equations and to systems of linear differential equations with varying coefficients. Fundamentals of Advanced Mathematics, Volume 2: Field Extensions, Topology and Topological Vector Spaces, Functional Spaces, and Sheaves begins with the classical Galois theory and the theory of transcendental field extensions. Next, the differential side of these theories is treated, including the differential Galois theory (Picard-Vessiot theory of systems of linear differential equations with time-varying coefficients) and differentially transcendental field extensions. The treatment of analysis includes topology (using both filters and nets), topological vector spaces (using the notion of disked space, which simplifies the theory of duality), and the radon measure (assuming that the usual theory of measure and integration is known). In addition, the theory of sheaves is developed with application to the theory of distributions and the theory of hyperfunctions (assuming that the usual theory of functions of the complex variable is known). This volume is the prerequisite to the study of linear systems with time-varying coefficients from the point-of-view of algebraic analysis and the algebraic theory of nonlinear systems.

Occupancy Estimation and Modeling

  • 2nd Edition
  • November 13, 2017
  • Darryl I. MacKenzie + 5 more
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 8 1 4 6 9 1 - 0
  • eBook
    9 7 8 - 0 - 1 2 - 4 0 7 2 4 5 - 9
Occupancy Estimation and Modeling: Inferring Patterns and Dynamics of Species Occurrence, Second Edition, provides a synthesis of model-based approaches for analyzing presence-absence data, allowing for imperfect detection. Beginning from the relatively simple case of estimating the proportion of area or sampling units occupied at the time of surveying, the authors describe a wide variety of extensions that have been developed since the early 2000s. This provides an improved insight about species and community ecology, including, detection heterogeneity; correlated detections; spatial autocorrelation; multiple states or classes of occupancy; changes in occupancy over time; species co-occurrence; community-level modeling, and more. Occupancy Estimation and Modeling: Inferring Patterns and Dynamics of Species Occurrence, Second Edition has been greatly expanded and detail is provided regarding the estimation methods and examples of their application are given. Important study design recommendations are also covered to give a well rounded view of modeling.

Fundamentals of Advanced Mathematics 1

  • 1st Edition
  • July 1, 2017
  • Henri Bourles
  • English
  • Hardback
    9 7 8 - 1 - 7 8 5 4 8 - 1 7 3 - 4
  • eBook
    9 7 8 - 0 - 0 8 - 1 0 2 1 1 2 - 5
This precis, comprised of three volumes, of which this book is the first, exposes the mathematical elements which make up the foundations of a number of contemporary scientific methods: modern theory on systems, physics and engineering. This first volume focuses primarily on algebraic questions: categories and functors, groups, rings, modules and algebra. Notions are introduced in a general framework and then studied in the context of commutative and homological algebra; their application in algebraic topology and geometry is therefore developed. These notions play an essential role in algebraic analysis (analytico-algebraic systems theory of ordinary or partial linear differential equations). The book concludes with a study of modules over the main types of rings, the rational canonical form of matrices, the (commutative) theory of elemental divisors and their application in systems of linear differential equations with constant coefficients.

Inequalities and Extremal Problems in Probability and Statistics

  • 1st Edition
  • May 8, 2017
  • Iosif Pinelis + 4 more
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 8 0 9 8 1 8 - 9
  • eBook
    9 7 8 - 0 - 1 2 - 8 0 9 8 9 2 - 9
Inequalities and Extremal Problems in Probability and Statistics: Selected Topics presents various kinds of useful inequalities that are applicable in many areas of mathematics, the sciences, and engineering. The book enables the reader to grasp the importance of inequalities and how they relate to probability and statistics. This will be an extremely useful book for researchers and graduate students in probability, statistics, and econometrics, as well as specialists working across sciences, engineering, financial mathematics, insurance, and mathematical modeling of large risks.

Survey Sampling Theory and Applications

  • 1st Edition
  • March 8, 2017
  • Raghunath Arnab
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 8 1 1 8 4 8 - 1
  • eBook
    9 7 8 - 0 - 1 2 - 8 1 1 8 9 7 - 9
Survey Sampling Theory and Applications offers a comprehensive overview of survey sampling, including the basics of sampling theory and practice, as well as research-based topics and examples of emerging trends. The text is useful for basic and advanced survey sampling courses. Many other books available for graduate students do not contain material on recent developments in the area of survey sampling. The book covers a wide spectrum of topics on the subject, including repetitive sampling over two occasions with varying probabilities, ranked set sampling, Fays method for balanced repeated replications, mirror-match bootstrap, and controlled sampling procedures. Many topics discussed here are not available in other text books. In each section, theories are illustrated with numerical examples. At the end of each chapter theoretical as well as numerical exercises are given which can help graduate students.

Ruin Probabilities

  • 1st Edition
  • October 10, 2016
  • Yuliya Mishura + 1 more
  • English
  • Hardback
    9 7 8 - 1 - 7 8 5 4 8 - 2 1 8 - 2
  • eBook
    9 7 8 - 0 - 0 8 - 1 0 2 0 9 8 - 2
Ruin Probabilities: Smoothness, Bounds, Supermartingale Approach deals with continuous-time risk models and covers several aspects of risk theory. The first of them is the smoothness of the survival probabilities. In particular, the book provides a detailed investigation of the continuity and differentiability of the infinite-horizon and finite-horizon survival probabilities for different risk models. Next, it gives some possible applications of the results concerning the smoothness of the survival probabilities. Additionally, the book introduces the supermartingale approach, which generalizes the martingale one introduced by Gerber, to get upper exponential bounds for the infinite-horizon ruin probabilities in some generalizations of the classical risk model with risky investments.

Environmental Data Analysis with MatLab

  • 2nd Edition
  • March 7, 2016
  • William Menke + 1 more
  • English
  • Hardback
    9 7 8 - 0 - 1 2 - 8 0 4 4 8 8 - 9
  • eBook
    9 7 8 - 0 - 1 2 - 8 0 4 5 5 0 - 3
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. Since publication of the bestselling Environmental Data Analysis with MATLAB®, many advances have been made in environmental data analysis. One only has to consider the global warming debate to realize how critically important it is to be able to derive clear conclusions from often noisy data drawn from a broad range of sources. The work teaches the basics of the underlying theory of data analysis and then reinforces that knowledge with carefully chosen, realistic scenarios. MATLAB®, a commercial data processing environment, is used in these scenarios. Significant content is devoted to teaching how it can be effectively used in an environmental data analysis setting. This new edition, though written in a self-contained way, is supplemented with data and MATLAB® scripts that can be used as a data analysis tutorial. New features include boxed crib sheets to help identify major results and important formulas and give brief advice on how and when they should be used. Numerical derivatives and integrals are derived and illustrated. Includes log-log plots with further examples of their use. Discusses new datasets on precipitation and stream flow. Topical enhancement applies the chi-squared test to the results of the generalized least squares method. New coverage of cluster analysis and approximation techniques that are widely applied in data analysis, including Taylor Series and low-order polynomial approximations; non-linear least-squares with Newton’s method; and pre-calculation and updating techniques applicable to real time data acquisition.

An Introduction to Stochastic Orders

  • 1st Edition
  • September 21, 2015
  • Felix Belzunce + 2 more
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 8 0 3 7 6 8 - 3
  • eBook
    9 7 8 - 0 - 1 2 - 8 0 3 8 2 6 - 0
An Introduction to Stochastic Orders discusses this powerful tool that can be used in comparing probabilistic models in different areas such as reliability, survival analysis, risks, finance, and economics. The book provides a general background on this topic for students and researchers who want to use it as a tool for their research. In addition, users will find detailed proofs of the main results and applications to several probabilistic models of interest in several fields, and discussions of fundamental properties of several stochastic orders, in the univariate and multivariate cases, along with applications to probabilistic models.

Stochastic Calculus for Quantitative Finance

  • 1st Edition
  • August 19, 2015
  • Alexander A Gushchin
  • English
  • Hardback
    9 7 8 - 1 - 7 8 5 4 8 - 0 3 4 - 8
  • eBook
    9 7 8 - 0 - 0 8 - 1 0 0 4 7 6 - 0
In 1994 and 1998 F. Delbaen and W. Schachermayer published two breakthrough papers where they proved continuous-time versions of the Fundamental Theorem of Asset Pricing. This is one of the most remarkable achievements in modern Mathematical Finance which led to intensive investigations in many applications of the arbitrage theory on a mathematically rigorous basis of stochastic calculus.Mathematical Basis for Finance: Stochastic Calculus for Finance provides detailed knowledge of all necessary attributes in stochastic calculus that are required for applications of the theory of stochastic integration in Mathematical Finance, in particular, the arbitrage theory. The exposition follows the traditions of the Strasbourg school. This book covers the general theory of stochastic processes, local martingales and processes of bounded variation, the theory of stochastic integration, definition and properties of the stochastic exponential; a part of the theory of Lévy processes. Finally, the reader gets acquainted with some facts concerning stochastic differential equations.