Harmonic Functions and Random Walks on Groups
Research in recent years has highlighted the deep connections between the algebraic, geometric, and analytic structures of a discrete group. New methods and ideas have resulted in an exciting field, with many opportunities for new researchers. This book is an introduction to the area from a modern vantage point. It incorporates the main basics, such as Kesten's amenability criterion, Coulhon and Saloff-Coste inequality, random walk entropy and bounded harmonic functions, the Choquet-Deny Theorem, the Milnor-Wolf Theorem, and a complete proof of Gromov's Theorem on polynomial growth groups. The book is especially appropriate for young researchers, and those new to the field, accessible even to graduate students. An abundance of examples, exercises, and solutions encourage self-reflection and the internalization of the concepts introduced. The author also points to open problems and possibilities for further research.
Ecosystem Modelling with EwE
This textbook provides a basis for courses in ecosystem modelling based on the Ecopath with Ecosim (EwE) modelling framework and software. EwE is a versatile approach with a low but very long (and gradually steeper) learning curve.The authors have been central to the development of EwE for more than thirty years, and during that time the simple Ecopath mass-balance approach it started with has through the addition of time and spatial-dynamic models, among others, been expanded to become a dynamic toolbox that can be used to address anything from simple fundamental research questions to very complex management and policy questions related to ecosystem based management.It's been a guiding principle throughout the development of EwE to provide an easy-to-access approach that does not require extensive mathematical or programming capabilities to get start. Model first, ask later is the philosophy. By just getting started with modelling, you gain insight and can start asking fundamental questions about how components of ecosystems interplay. Diving deeper is important, but this textbook makes the initial getting-started as simple and accessible as possible.
Probability Theory
This book is intended as an introduction to Probability Theory and Mathematical Statistics for students in mathematics, the physical sciences, engineering, and related fields. It is based on the author's 25 years of experience teaching probability and is squarely aimed at helping students overcome common difficulties in learning the subject. The focus of the book is an explanation of the theory, mainly by the use of many examples. Whenever possible, proofs of stated results are provided. All sections conclude with a short list of problems. The book also includes several optional sections on more advanced topics. This textbook would be ideal for use in a first course in Probability Theory. Contents: ProbabilitiesConditional Probabilities and IndependenceRandom Variables and Their DistributionOperations on Random VariablesExpected Value, Variance, and CovarianceNormally Distributed Random VectorsLimit Theorems Introduction to Stochastic ProcessesMathematical StatisticsAppendixBibliographyIndex
Practical Machine Learning with R
This textbook is a comprehensive guide to machine learning and artificial intelligence tailored for students in business and economics. It takes a hands-on approach to teach machine learning, emphasizing practical applications over complex mathematical concepts. Students are not required to have advanced mathematics knowledge such as matrix algebra or calculus.The author introduces machine learning algorithms, utilizing the widely used R language for statistical analysis. Each chapter includes examples, case studies, and interactive tutorials to enhance understanding. No prior programming knowledge is needed. The book leverages the tidymodels package, an extension of R, to streamline data processing and model workflows. This package simplifies commands, making the logic of algorithms more accessible by minimizing programming syntax hurdles. The use of tidymodels ensures a unified experience across various machine learning models.With interactive tutorials that students can download and follow along at their own pace, the book provides a practical approach to apply machine learning algorithms to real-world scenarios.In addition to the interactive tutorials, each chapter includes a Digital Resources section, offering links to articles, videos, data, and sample R code scripts. A companion website further enriches the learning and teaching experience: https: //ai.lange-analytics.com.This book is not just a textbook; it is a dynamic learning experience that empowers students and instructors alike with a practical and accessible approach to machine learning in business and economics. Key Features: Unlocks machine learning basics without advanced mathematics -- no calculus or matrix algebra required. Demonstrates each concept with R code and real-world data for a deep understanding -- no prior programming knowledge is needed. Bridges the gap between theory and real-world applications with hands-on interactive projects and tutorials in every chapter, guided with hints and solutions. Encourages continuous learning with chapter-specific online resources--video tutorials, R-scripts, blog posts, and an online community. Supports instructors through a companion website that includes customizable materials such as slides and syllabi to fit their specific course needs.
A Technical Guide to Mathematical Finance
This book covers those mathematical topics most important to an aspiring or professional quant. The text goes beyond a simple recitation of methods and aims to impart a genuine understanding of the fundamental concepts underpinning most of the techniques and tools routinely used by those working in quantitative finance.
Encounters with Chaos and Fractals
Encounters with Chaos and Fractals, Third Edition provides an accessible introduction to chaotic dynamics and fractal geometry. It incorporates important mathematical concepts and backs up the definitions and results with motivation, examples, and applications.
Mathematical Puzzles
Research in maths is much more than solving puzzles, but most people will agree that solving puzzles is not just fun: it helps focus the mind and increases one's armory of techniques for doing maths. This book makes this connection explicit by isolating important mathematical methods, then using them to solve puzzles and prove a theorem.
Mathematical Puzzles
Research in maths is much more than solving puzzles, but most people will agree that solving puzzles is not just fun: it helps focus the mind and increases one's armory of techniques for doing maths. This book makes this connection explicit by isolating important mathematical methods, then using them to solve puzzles and prove a theorem.
Topics in Model Theory
This book has two chapters. The first is a modern or contemporary account of stability theory. A focus is on the local (formula-by-formula) theory, treated a little differently from in the author's book Geometric Stability Theory. There is also a survey of general and geometric stability theory, as well as applications to combinatorics (stable regularity lemma) using pseudofinite methods.The second is an introduction to 'continuous logic' or 'continuous model theory, ' drawing on the main texts and papers, but with an independent point of view. This chapter includes some historical background, including some other formalisms for continuous logic and a discussion of hyperimaginaries in classical first order logic.These chapters are based around notes, written by students, from a couple of advanced graduate courses in the University of Notre Dame, in Autumn 2018, and Spring 2021.
Topics in Model Theory
This book has two chapters. The first is a modern or contemporary account of stability theory. A focus is on the local (formula-by-formula) theory, treated a little differently from in the author's book Geometric Stability Theory. There is also a survey of general and geometric stability theory, as well as applications to combinatorics (stable regularity lemma) using pseudofinite methods.The second is an introduction to 'continuous logic' or 'continuous model theory, ' drawing on the main texts and papers, but with an independent point of view. This chapter includes some historical background, including some other formalisms for continuous logic and a discussion of hyperimaginaries in classical first order logic.These chapters are based around notes, written by students, from a couple of advanced graduate courses in the University of Notre Dame, in Autumn 2018, and Spring 2021.
Model-Based Monitoring and Statistical Control
Available in English for the first time, this classic and influential book by the late Kohei Otshu presents real examples of ships in motion under irregular ocean waves, helping to expalin fluctuations of stochastic phenomena through spectral analysis methods and statistical modeling.
Causal Inference in Pharmaceutical Statistics
Causal Inference in Pharmaceutical Statistics introduces the basic concepts and fundamental methods of causal inference relevant to pharmaceutical statistics. This book covers causal thinking for different types of commonly used study designs in the pharmaceutical industry, including but not limited to randomized controlled clinical trials, longitudinal studies, singlearm clinical trials with external controls, and real-world evidence studies. The book starts with the central questions in drug development and licensing, takes the reader through the basic concepts and methods via different study types and through different stages, and concludes with a roadmap to conduct causal inference in clinical studies. The book is intended for clinical statisticians and epidemiologists working in the pharmaceutical industry. It will also be useful to graduate students in statistics, biostatistics, and data science looking to pursue a career in the pharmaceutical industry.Key Features: Causal inference book for clinical statisticians in the pharmaceutical industry Introductory level on the most important concepts and methods Align with FDA and ICH guidance documents Across different stages of clinical studies: plan, design, conduct, analysis, and interpretation Cover a variety of commonly used study designs
The Polls Weren't Wrong
This book will equip readers with the tools to navigate the mismatch of expectations. It is not intended to replace more technical applications of statistics but is accessible to those interested in learning about how poll data should be understood.
Ordinal Data Analysis
This book is a step-by-step data story for analysing ordinal data from start to finish. The book is for researchers, statisticians and scientists who are working with data sets where the response is ordinal. This type of data is common in many disciplines, not just in surveys.
Nonparametric Statistical Methods Using R
This thoroughly updated and expanded second edition covers traditional nonparametric methods and rank-based analyses. Two new chapters covering multivariate analyses and big data have been added. Core classical nonparametrics chapters on one- and two-sample problems have been expanded
Fundamentals of Order and Rank Statistics
This book is devoted to the fundamentals of order and rank statistics. Primarily focusing on theoretical properties, it also discusses practical aspects, including interesting applications of step and impulse functions for the distribution of random variables, magnitudes, and signs. New concepts are introduced, such as independent and semi-identically distributed random vectors and probability density-mass functions. This book also presents an investigation of relative magnitudes in order statistics, and of correlation coefficients among signs, ranks, and magnitudes. The basic concepts are described in clear terms, and step-by-step details are provided for most of the presented mathematical results. The exposition is accompanied by numerous examples and more than 100 exercises, for which a complete solution manual is available. Providing a useful reference, and requiring only a basic understanding of probability and random variables, the book will appeal to a wide readership.
Nonlinear Second Order Elliptic Equations
This book focuses on the following three topics in the theory of boundary value problems of nonlinear second order elliptic partial differential equations and systems: (i) eigenvalue problem, (ii) upper and lower solutions method, (iii) topological degree method, and deals with the existence of solutions, more specifically non-constant positive solutions, as well as the uniqueness, stability and asymptotic behavior of such solutions.While not all-encompassing, these topics represent major approaches to the theory of partial differential equations and systems, and should be of significant interest to graduate students and researchers. Two appendices have been included to provide a good gauge of the prerequisites for this book and make it reasonably self-contained.A notable strength of the book is that it contains a large number of substantial examples. Exercises for the reader are also included. Therefore, this book is suitable as a textbook for graduate students who havealready had an introductory course on PDE and some familiarity with functional analysis and nonlinear functional analysis, and as a reference for researchers.
Simulation and Statistics with Excel
Simulation and Statistics with Excel: An Introduction to Business Students uses a versatile and accessible resource, the Microsoft Excel spreadsheet, to cover the concepts essential to understanding the basic principles and approaches of statistical simulation
Statistical Thinking in Clinical Trials
The authors present the essence of statistical reasoning in clinical trials, peppered with well-known clinical trials This book uses only a small number of important principles to develop the entire statistical foundation of clinical trials.
Recent Trends in AI Enabled Technologies
This book constitutes the refereed proceedings of the First International Conference on Recent Trends in AI Enabled Technologies, ThinkAI 2023, which took place in Hyderabad, India, in December 2023. The 7 full papers presented in these proceedings were carefully reviewed and selected from 51 submissions. The conference focuses on on up to date topics and recent trends in artificial intelligence and related technologies.
From Concepts to Code
The breadth of problems that can be solved with data science is astonishing, and this book provides the required tools and skills to a broad audience. The necessary background in computer science, mathematics, and statistics is provided in an approachable manner.
Dynamic Network Flows with Adaptive Route Choice Based on Current Information
In this book Lukas Graf studies dynamic network flows which are a model for individual car traffic in road networks. It is assumed that drivers choose their routes based on information about the current state of the network in such a way as to selfishly minimize their own arrival time at their destination. Whilst on their journey the drivers adapt their current route choices based on the changing state of the network. A dynamic flow wherein every (infinitesimally small) flow particle behaves in this way is then called an instantaneous dynamic equilibrium. After giving a mathematically precise definition of this equilibrium concept the author shows existence of those equilibrium flows, studies their computational complexity and derives bounds on their quality.
Mathematical Sciences and Applications
The papers appearing in these proceedings are part of talks, oral presentations and poster presentations given at the International Conference on Mathematical Sciences and Applications held in the Department of Mathematics, Dr. Bhimrao Ambedkar University, Agra (India) from March 24-26, 2023.
Numerical Methods for Scientists and Engineers
This book is designed as a primary textbook for a one-semester course on Numerical Methods for sophomore or junior-level students. It covers the fundamental numerical methods required for scientists and engineers, as well as some advanced topics which are left to the discretion of instructors.
Actuarial Loss Models
This book covers part of the learning outcomes of the Fundamentals of Actuarial Mathematics (FAM) exam and the Advanced Short-Term Actuarial Mathematics (ASTAM) exam administered by the Society of Actuaries. It can be used by students and practitioners who prepare for actuarial exams.
The Eternal Life
Applied Math to Life ResearchUsing the objectiveness of the Mathematical Language to analyze, study and conclude on the spiritual eternal life, the successive lifetimes, life, death and related subjects.A "must not miss" book, quite deep on its subjects but joyfully presented on a youngish style.
Reliability
This text provides an elementary introduction to the probabilistic models and statistical methods used by reliability engineers that are applied to a system of components. Probability models include the exponential distribution, Weibull distribution, competing risks, mixtures, accelerated life model, proportional hazards model, and repairable systems models. Statistical methods emphasize determining point and interval estimates for parameters from censored data sets. Applications are drawn from a variety of disciplines. Over 600 exercises make this text appropriate for a class on reliability.
Functional Analysis with Applications
This book on functional analysis covers all the basics of the subject (normed, Banach and Hilbert spaces, Lebesgue integration and spaces, linear operators and functionals, compact and self-adjoint operators, small parameters, fixed point theory) with a strong focus on examples, exercises and practical problems, thus making it ideal as course material but also as a reference for self-study.
Complex Analysis
This book is an in-depth and modern presentation of important classical results in complex analysis and is suitable for a first course on the topic, as taught by the authors at several universities. The level of difficulty of the material increases gradually from chapter to chapter, and each chapter contains many exercises with solutions and applications of the results, with the particular goal of showcasing a variety of solution techniques.
Single Variable Calculus
A computer algebra system such as Mathematica(R) is able to do much more than just numerics: This text shows how to tackle real mathematical problems from basic analysis. The reader learns how Mathematica(R) represents domains, qualifiers and limits to implement actual proofs - a requirement to unlock the huge potential of Mathematica(R) for a variety of applications.
Martingale Methods in Statistics
This gives a comprehensive introduction to the (standard) statistical analysis based on the theory of martingales and develops entropy methods in order to treat dependent data in the framework of martingales. The author starts a summary of the martingale theory, and then proceeds to give full proofs of the martingale central limit theorems.
Beyond Multiple Linear Regression
For advanced undergraduate or non-major graduate students in Advanced Statistical Modeling or Regression II and courses in Generalized Linear Models, Longitudinal Data Analysis, Correlated Data, Multilevel Models. Material on R at the end of each chapter. Solutions manual for qualified instructors.
Analysis of Distributional Data
In a time when increasingly larger and complex data collections are being produced, it is clear that new and adaptive forms of data representation and analysis have to be conceived and implemented. Distributional data, i.e., data where a distribution rather than a single value is recorded for each descriptor, on each unit, come into this framework. Distributional data may result from the aggregation of large amounts of open/collected/generated data, or it may be directly available in a structured or unstructured form, describing the variability of some features. This book provides models and methods for the representation, analysis, interpretation, and organization of distributional data, taking into account its specific nature, and not relying on a reduction to single values, to be conform to classical paradigms. Conceived as an edited book, gathering contributions from multiple authors, the book presents alternative representations and analysis' methods for distributional data of different types, and in particular, -Uni- and bi-variate descriptive statistics for distributional data-Clustering and classification methodologies-Methods for the representation in low-dimensional spaces-Regression models and forecasting approaches for distribution-valued variablesFurthermore, the different chapters -Feature applications to show how the proposed methods work in practice, and how results are to be interpreted, -Often provide information about available software.The methodologies presented in this book constitute cutting-edge developments for stakeholders from all domains who produce and analyse large amounts of complex data, to be analysed in the form of distributions. The book is hence of interest for companies operating not only in the area of data analytics, but also on logistics, energy and finance. It also concerns national statistical institutes and other institutions at European and international level, where microdata is aggregated to preserve confidentiality and allow for analysis at the appropriate regional level. Academics will find in the analysis of distributional data a challenging up-to-date field of research.
Analysis of Longitudinal Data with Examples
Development in methodology on longitudinal data is fast. Currently, there are a lack of intermediate /advanced level textbooks which introduce students and practicing statisticians to the updated methods on correlated data inference. This book will present a discussion of the modern approaches to inference, including the links between the theories of estimators and various types of efficient statistical models including likelihood-based approaches. The theory will be supported with practical examples of R-codes and R-packages applied to interesting case-studies from a number of different areas.Key Features: -Includes the most up-to-date methods-Use simple examples to demonstrate complex methods-Uses real data from a number of areas-Examples utilize R code
Principles of Uncertainty
Like the De Groot winning first edition, the second edition of Principles of Uncertainty is an accessible, comprehensive guide to the theory of Bayesian Statistics written in an appealing, inviting style, and packed with interesting examples.
Mathematics of Information
Ausgehend vom Shannon-Wiener-Zugang zur mathematischen Informationstheorie beginnt das Buch mit einer Abgrenzung der Begriffe Nachricht und Information und der axiomatischen Zuordnung einer Informationsmenge zu einer Wahrscheinlichkeit. Im zweiten Teil werden abz瓣hlbare Wahrscheinlichkeitsr瓣ume untersucht, deren mittlere Informationsmenge zur Definition der Shannon-Entropie f羹hrt; dabei werden drei klassische Anwendungen der Shannon-Entropie in der statistischen Physik, der mathematischen Statistik und der Nachrichtentechnik vorgestellt, und es wird ein erster Einblick in den Bereich Quanteninformation gegeben. Der dritte Teil behandelt die informationstheoretische Analyse dynamischer Systeme.Das Buch baut auf Bachelor-Wissen auf und legt gro?en Wert auf exakte Beweisf羹hrung.
Disruptive Technologies and Optimization Towards Industry 4.0 Logistics
This contributed volume guides researchers and practitioners on resource collaborative management of supply chains and manufacturing enterprises within an industrial internet technological environment. The book comprises 10 chapters that cover two major topics in the subject of logistics 4.0, namely the utilization of both disruptive technologies and optimization techniques in smart logistic management. With global research on the book's topic expanding rapidly across various directions and disciplines, it provides a structured framework for international experts to showcase outstanding work and unique approaches. Researchers and students will find the comprehensive outline on collaborative optimization and management of smart manufacturing and production, warehousing, inventory, logistics, transportation, integrated supply chain, and supply network within the industrial internet platform a beneficial guide to understanding current and future practical problems that arise in manufacturing and supply chain management.
Physical and Physiological Analysis of Soya Seeds from the 2016/2017 Harvest
The use of high quality seeds allows access to genetic advances, with guarantees of quality and adaptation technologies in the various producing regions. The factors that influence seed quality can occur during the production phase in the field, during harvesting, drying, processing, storage, transport and sowing. Quality control must therefore be established, which includes analysing and certifying the seed in order to guarantee the genetic purity of the cultivars, thus assuring the farmer of a pure batch with high vigour, which can establish a uniform stand in the field. The quality of soya bean seed is essential for obtaining an adequate plant stand, because when the seed is placed in the soil to germinate and emerge, it usually encounters adverse conditions of humidity and temperature, among other factors. Considering the importance of seed for agricultural production and aiming to achieve higher levels of profitability, this study will present data on the physical and physiological quality of soya bean seeds from the 2017/2018 harvest in northern Rio Grande do Sul.
Proceedings of the Sixth Berkeley Symposium on Mathematical Statistics and Probability, Volume III
This title is part of UC Press's Voices Revived program, which commemorates University of California Press's mission to seek out and cultivate the brightest minds and give them voice, reach, and impact. Drawing on a backlist dating to 1893, Voices Revived makes high-quality, peer-reviewed scholarship accessible once again using print-on-demand technology. This title was originally published in 1972.
Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability, Volume II, Part II
This title is part of UC Press's Voices Revived program, which commemorates University of California Press's mission to seek out and cultivate the brightest minds and give them voice, reach, and impact. Drawing on a backlist dating to 1893, Voices Revived makes high-quality, peer-reviewed scholarship accessible once again using print-on-demand technology. This title was originally published in 1967.
Proceedings of the Sixth Berkeley Symposium on Mathematical Statistics and Probability, Volume III
This title is part of UC Press's Voices Revived program, which commemorates University of California Press's mission to seek out and cultivate the brightest minds and give them voice, reach, and impact. Drawing on a backlist dating to 1893, Voices Revived makes high-quality, peer-reviewed scholarship accessible once again using print-on-demand technology. This title was originally published in 1972.
Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability, Volume II, Part II
This title is part of UC Press's Voices Revived program, which commemorates University of California Press's mission to seek out and cultivate the brightest minds and give them voice, reach, and impact. Drawing on a backlist dating to 1893, Voices Revived makes high-quality, peer-reviewed scholarship accessible once again using print-on-demand technology. This title was originally published in 1967.
Game Theory and Applications
This textbook provides an overview of the fundamentals of game theory and its applications in various fields. It introduces game theory as an established toolkit for the mathematical analysis and evaluation of strategic decisions. Through applied exercises, it introduces the basic concepts of game theory and offers students from various disciplines the opportunity to practice the concepts through in-depth training. The textbook addresses advanced students of economics, business administration, and related disciplines, university graduates with basic mathematical training as well as interested readers from all fields. For this, it provides student-friendly explanations, a variety of exercises and problems, and useful references to further reading. The book is divided into a beginner-friendly theory section, in which the most important aspects are presented in a compact and clear manner, and an application-oriented problem section, in which the readers can directly check what they have learned and find many application examples. The latter can also be used as a source of inspiration for instructors.
Finite Difference Methods on Irregular Networks
No detailed description available for "Finite Difference Methods on Irregular Networks".
