Providing a much-needed bridge between elementary statistics courses and advanced research methods courses, Understanding Advanced Statistical Methods helps students grasp the fundamental assumptions and machinery behind sophisticated statistical topics, such as logistic regression, maximum likelihood, bootstrapping, nonparametrics, and Bayesian me
An Introductory Econometrics TextMathematical Statistics for Applied Econometrics covers the basics of statistical inference in support of a subsequent course on classical econometrics.
While there have been few theoretical contributions on the Markov Chain Monte Carlo (MCMC) methods in the past decade, current understanding and application of MCMC to the solution of inference problems has increased by leaps and bounds.
Retaining all the material from the second edition and adding substantial new material, this third edition presents models and statistical methods for analyzing spatially referenced point process data.
This book investigates the critical gain design in stochastic iterative learning control (SILC), including four specific gain design strategies: decreasing gain design, adaptive gain design, event-triggering gain design, and optimal gain design.
This textbook, which is based on the second edition of a book that has been previously published in German language, provides a comprehension-oriented introduction to asymptotic stochastics.
This book investigates the critical gain design in stochastic iterative learning control (SILC), including four specific gain design strategies: decreasing gain design, adaptive gain design, event-triggering gain design, and optimal gain design.
This textbook, which is based on the second edition of a book that has been previously published in German language, provides a comprehension-oriented introduction to asymptotic stochastics.
Statistical and Probabilistic Methods in Actuarial Science covers many of the diverse methods in applied probability and statistics for students aspiring to careers in insurance, actuarial science, and finance.
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 presents the theory of rational decisions involving the selection of stopping times in observed discrete-time stochastic processes, both by single and multiple decision-makers.
This book provides a practical guide on annotating emotions in natural language data and showcases how these annotations can improve Natural Language Processing (NLP) and Natural Language Understanding (NLU) models and applications.
This book provides a practical guide on annotating emotions in natural language data and showcases how these annotations can improve Natural Language Processing (NLP) and Natural Language Understanding (NLU) models and applications.
This book presents the proceedings of the international conference Particle Systems and Partial Differential Equations X, which was held at the University of Minho, Braga, Portugal, from 2022.
This book presents the proceedings of the international conference Particle Systems and Partial Differential Equations X, which was held at the University of Minho, Braga, Portugal, from 2022.
Highlighting modern computational methods, Applied Stochastic Modelling, Second Edition provides students with the practical experience of scientific computing in applied statistics through a range of interesting real-world applications.
This book provides a rigorous introduction to the theory, computation, and applications of variational inequalities (VIs), with a focus on applications in management science and finance.
Dieses Lehrbuch wendet sich hauptsächlich an Studierende der Ingenieur- und Naturwissenschaften sowie der Informatik, aber auch an in der angewandten Praxis tätige Fachkräfte in diesen Disziplinen.
Offering a unique balance between applications and calculations, Monte Carlo Methods and Models in Finance and Insurance incorporates the application background of finance and insurance with the theory and applications of Monte Carlo methods.
Applied Probability presents a unique blend of theory and applications, with special emphasis on mathematical modeling, computational techniques, and examples from the biological sciences.
Applied Probability presents a unique blend of theory and applications, with special emphasis on mathematical modeling, computational techniques, and examples from the biological sciences.
Filling the need for an introductory book on linear programming that discusses the important ways to mitigate parameter uncertainty, Introduction to Linear Optimization and Extensions with MATLAB provides a concrete and intuitive yet rigorous introduction to modern linear optimization.
Bayesian Missing Data Problems: EM, Data Augmentation and Noniterative Computation presents solutions to missing data problems through explicit or noniterative sampling calculation of Bayesian posteriors.
Mit diesem Buch gelingt dem Autor des bekannten Lehrwerkes Stochastik für Einsteiger auf geradezu spielerische Weise, den Leser mit zahlreichen überraschenden Zufallsphänomenen und Nicht-Standard-Grenzwertsätzen im Zusammenhang mit einfachen Irrfahrten und verwandten Themen zu fesseln.
Probability Models, Volume 51 in the Handbook of Statistics series, highlights new advances in the field, with this new volume presenting interesting chapters on Stein's methods, Probabilities and thermodynamics third law, Random Matrix Theory, General tools for understanding fluctuations of random variables, An approximation scheme to compute the Fisher-Rao distance between multivariate normal distributions, Probability Models Applied to Reliability and Availability Engineering, Backward stochastic differential equation- Stochastic optimization theory and viscous solution of HJB equation, and much more.
Mit diesem Buch gelingt dem Autor des bekannten Lehrwerkes Stochastik für Einsteiger auf geradezu spielerische Weise, den Leser mit zahlreichen überraschenden Zufallsphänomenen und Nicht-Standard-Grenzwertsätzen im Zusammenhang mit einfachen Irrfahrten und verwandten Themen zu fesseln.
Incorporating a collection of recent results, Polya Urn Models deals with discrete probability through the modern and evolving urn theory and its numerous applications.
This book studies a general class of convex stochastic optimization (CSO) problems that unifies many common problem formulations from operations research, financial mathematics and stochastic optimal control.
This book studies a general class of convex stochastic optimization (CSO) problems that unifies many common problem formulations from operations research, financial mathematics and stochastic optimal control.
The application of engineering principles in divergent fields such as management science and communications as well as the advancement of several approaches in theory and computation have led to growing interest in queueing models, creating the need for a comprehensive text.
Filling the void between surveys of the field with relatively light mathematical content and books with a rigorous, formal approach to stochastic integration and probabilistic ideas, Stochastic Financial Models provides a sound introduction to mathematical finance.
Integrating interesting and widely used concepts of financial engineering into traditional statistics courses, Introduction to Probability and Statistics for Science, Engineering, and Finance illustrates the role and scope of statistics and probability in various fields.
Arbeitsbuch Stochastik (Einführung und Grundzüge der Maßtheorie)
Dieses Arbeitsbuch enthält die Aufgaben, Hinweise, Lösungen und Lösungswege der Kapitel 2 bis 8 des Lehrbuchs Stochastik: Eine Einführung mit Grundzügen der Maßtheorie.
An Introduction to Stochastic Processes with Applications to Biology, Second Edition presents the basic theory of stochastic processes necessary in understanding and applying stochastic methods to biological problems in areas such as population growth and extinction, drug kinetics, two-species competition and predation, the spread of epidemics, and
A Cohesive Approach to Regression ModelsConfidence Intervals in Generalized Regression Models introduces a unified representation-the generalized regression model (GRM)-of various types of regression models.
