R for Conservation and Development Projects
This book is aimed at conservation and development practitioners who need to learn and use R in a part-time professional context. It gives people with a non-technical background a set of skills to graph, map, and model in R. It also provides background on data integration in project management and covers fundamental statistical concepts. The book aims to demystify R and give practitioners the confidence to use it. Key Features: - Viewing data science as part of a greater knowledge and decision making system - Foundation sections on inference, evidence, and data integration - Plain English explanations of R functions - Relatable examples which are typical of activities undertaken by conservation and development organisations in the developing world - Worked examples showing how data analysis can be incorporated into project reports
Bayesian Approaches in Oncology Using R and Openbugs
The book focuses on building concepts and procedure to perform Bayesian in Oncology setup. It presents the roles of Bayesian in Oncology to clinical medicine in the context of substantive and current applications. This book will help readers interested in exploring, understanding, and solving oncology research queries through Bayesian.
An Introduction to Analysis
This widely popular textbook provides a mathematically rigorous introduction to analysis of real­valued functions of one variable. This intuitive, student-friendly text is written in a manner that will help to ease the transition from primarily computational to primarily theoretical maths.
Mathematical Finance
Taking continuous-time stochastic processes allowing for jumps as its starting and focal point, this book provides an accessible introduction to the stochastic calculus and control of semimartingales and explains the basic concepts of Mathematical Finance such as arbitrage theory, hedging, valuation principles, portfolio choice, and term structure modelling. It bridges thegap between introductory texts and the advanced literature in the field.Most textbooks on the subject are limited to diffusion-type models which cannot easily account for sudden price movements. Such abrupt changes, however, can often be observed in real markets. At the same time, purely discontinuous processes lead to a much wider variety of flexible and tractable models. This explains why processes with jumps have become an established tool in the statistics and mathematics of finance. Graduate students, researchers as well as practitioners will benefit from this monograph.
Nonlinear Systems and Their Remarkable Mathematical Structures
The book aims to describe some recent progress in nonlinear differential equations and nonlinear dynamical systems (both continuous and discrete).
Applied Directional Statistics
This book describes new data-driven methodologies and case studies.The primary targeted audience is researchers in statistics, as well as those in fundamental roles such as earth sciences, environmetrics, astrophysics, machine learning, image analysis and bioinformatics.
Parallel Computing for Data Science
This is one of the first parallel computing books to focus exclusively on parallel data structures, algorithms, software tools, and applications in data science. The book prepares readers to write effective parallel code in various languages and learn more about different R packages and other tools. It covers the classic "n observations, p varia
Handbook of Environmental and Ecological Statistics
This handbook focuses on the enormous literature applying statistical methodology and modelling to environmental and ecological processes.
Textbook of Clinical Trials in Oncology
This is a textbook on the design and analysis of cancer clinical trials. It opens with a discussion of the choice of endpoints before moving onto discuss various types of trials across all phases of study, including basket trials, non-inferiority trials and multi-arm trials.
Mathematical Theory of Bayesian Statistics
This book introduces the mathematical foundation of Bayesian statistics. It is well known that Bayesian inference is more accurate than the maximum likelihood method in many real-world problems: however, its mathematical foundations have been left unexplained. Recently, new research on Bayesian statistics uncovered the mathematical laws by which
Counterparty Risk and Funding
This book explains how to study risk embedded in financial transactions between the bank and its counterparty. The authors provide an analytical basis for the quantitative methodology of dynamic valuation, mitigation, and hedging of bilateral counterparty risk on over-the-counter (OTC) derivative contracts under funding constraints. They explore
Dynamical Biostatistical Models
This book presents statistical models and methods for the analysis of longitudinal data. It focuses on models for analyzing repeated measures of quantitative and qualitative variables and events history, including survival and multistate models. The book also explores the possibility of unifying these models through a stochastic process point of
Handbook of Missing Data Methodology
This handbook presents many methodological advances and the latest applications of missing data methods in empirical research. It outlines a general taxonomy of missing data mechanisms and their implications for analysis and describes alternatives for estimating models when data are missing. The book covers a range of approaches that assess the
Real Analysis
This book provides a resolution to the "bridging-the-gap problem." The book not only presents the fundamental theorems of real analysis, but also shows the reader how to compose and produce the proofs of these theorems.
Using R and Rstudio for Data Management, Statistical Analysis, and Graphics
This book covers the aspects of R most often used by statistical analysts. Incorporating the use of RStudio and the latest R packages, this second edition offers new chapters on simulation, special topics, and case studies. It reorganizes and enhances the chapters on data input and output, data management, statistical and mathematical functions,
Environmental and Ecological Statistics with R
Environmental and Ecological Statistics with R, Second Edition focuses on statistical modeling and data analysis for environmental and ecological problems. By guiding readers through the process of scientific problem solving and statistical model development, it eases the transition from scientific hypothesis to statistical mode
Analyzing Longitudinal Clinical Trial Data
Missing data in longitudinal clinical trials has justifiably been the target of considerable research. However, missing data is just one of the many considerations in the analysis of longitudinal data, and focus on the data we don't have should not distract from focus on the data we do have. The statistical theory relevant to analyses of longitu
Analysis of Variance, Design, and Regression
This second edition focuses on modeling unbalanced data. It presents many new topics, including new chapters on logistic regression, log-linear models, and time-to-event data. It shows how to model main-effects and interactions and introduces nonparametric, lasso, and generalized additive regression models. The text carefully analyzes small unba
Handbook of Graphical Models
A graphical model is a statistical model that is represented by a graph. The factorization properties underlying graphical models facilitate tractable computation with multivariate distributions, making the models a valuable tool with a plethora of applications. Furthermore, directed graphical models allow intuitive causal interpretations and have become a cornerstone for causal inference.While there exist a number of excellent books on graphical models, the field has grown so much that individual authors can hardly cover its entire scope. Moreover, the field is interdisciplinary by nature. Through chapters by leading researchers from different areas, this handbook provides a broad and accessible overview of the state of the art.Features: Contributions by leading researchers from a range of disciplines Structured in five parts, covering foundations, computational aspects, statistical inference, causal inference, and applications Balanced coverage of concepts, theory, methods, examples, and applications Chapters can be read mostly independently, while cross-references highlight connections The handbook is targeted at a wide audience, including graduate students, applied researchers, and experts in graphical models.
Analysis of Repeated Measures
Repeated measures data arise when the same characteristic is measured on each case or subject at several times or under several conditions. There is a multitude of techniques available for analysing such data and in the past this has led to some confusion. This book describes the whole spectrum of approaches, beginning with very simple and crude methods, working through intermediate techniques commonly used by consultant statisticians, and concluding with more recent and advanced methods. Those covered include multiple testing, response feature analysis, univariate analysis of variance approaches, multivariate analysis of variance approaches, regression models, two-stage line models, approaches to categorical data and techniques for analysing crossover designs. The theory is illustrated with examples, using real data brought to the authors during their work as statistical consultants.
Graphics for Statistics and Data Analysis with R
The book presents the basic principles of sound graphical design and applies these principles to engaging examples using the graphical functions available in R. It offers a wide variety of graphical displays for the presentation of data, including modern tools for data visualization and representation. The second edition will add examples with t
Nonparametric Statistics on Manifolds and Their Applications to Object Data Analysis
This book provides one of the first thorough treatments of the theory and methodology for analyzing data on manifolds. It also presents in-depth applications to practical problems arising in a variety of fields, including statistics, medical imaging, computer vision, pattern recognition, and bioinformatics. The authors introduce the relevant bac
Handbook of Biomarkers and Precision Medicine
Provides perspective, covers recent developments in technologies that have enabled the expanded use of biomarkers, discusses biomarker characterization and validation, and applications throughout the discovery-development continuum, including Companion Diagnostic ( CDX) development.
Statistical Methods for Field and Laboratory Studies in Behavioral Ecology
Statistical Methods for Field and Laboratory Studies in Behavioral Ecology focuses on how statistical methods may be used to make sense of behavioral ecology and other data. It presents fundamental concepts in statistical inference and intermediate topics such as multiple least squares regression and ANOVA. The objective is to teach students to recognize situations where various statistical methods should be used, understand the strengths and limitations of the methods, and to show how they are implemented in R code. Examples are based on research described in the literature of behavioral ecology, with data sets and analysis code provided. Features: This intermediate to advanced statistical methods text was written with the behavioral ecologist in mindComputer programs are provided, written in the R language.Datasets are also provided, mostly based, at least to some degree, on real studies.Methods and ideas discussed include multiple regression and ANOVA, logistic and Poisson regression, machine learning and model identification, time-to-event modeling, time series and stochastic modeling, game-theoretic modeling, multivariate methods, study design/sample size, and what to do when things go wrong.It is assumed that the reader has already had exposure to statistics through a first introductory course at least, and also has sufficient knowledge of R. However, some introductory material is included to aid the less initiated reader. Scott Pardo, Ph.D., is an accredited professional statistician (PStat(R)) by the American Statistical Association. Michael Pardo is a Ph.D. is a candidate in behavioral ecology at Cornell University, specializing in animal communication and social behavior.　　
Platform Trial Designs in Drug Development
Drug development sponsors cannot run individual trials for all products in all indications. This results in missed opportunities. Clinical trial programs known as "basket" and "umbrella" have demonstrated that multi-product, multi-indication trials can be efficient and feasible.
Bayesian Psychometric Modeling
This book presents a unified Bayesian approach across traditionally separate families of psychometric models. It shows that Bayesian techniques, as alternatives to conventional approaches, offer distinct and profound advantages in achieving many goals of psychometrics. The book covers foundational principles and statistical models as well as pop
Analysis of Incidence Rates
This book clarifies what incidence rates are, reviews their advantages and limitations, promotes understanding of analytic methods, describes what can be done in modern software, provides practical suggestions for analyses, and points out problems and pitfalls.
Handbook of Approximate Bayesian Computation
The Handbook of ABC provides illuminating insight into the world of Bayesian modelling for intractable models for both experts and newcomers alike. It is an essential reference book for anyone interested in learning about and implementing ABC techniques to analyse complex models in the modern world.
Advanced Regression Models with SAS and R
The material covered by this book consists of a collection of regression models beyond linear regression. The linear regression model is presented in the first chapter in order to refresh the reader's memory, emphasize certain points, and set the notation.The subsequent chapters talk about models for categorical data, count data, proportions, lo
Group Chase and Escape
This book presents a unique fusion of two different research topics. One is related to the traditional mathematical problem of chases and escapes. The problem mainly deals with a situation where a chaser pursues an evader to analyze their trajectories and capture time. It dates back more than 300 years and has developed in various directions such as differential games. The other topic is the recently developing field of collective behavior, which investigates origins and properties of emergent behavior in groups of self-driving units. Applications include schools of fish, flocks of birds, and traffic jams. This book first reviews representative topics, both old and new, from these two areas. Then it presents the combined research topic of "group chase and escape", recently proposed by the authors. Although the combination is simple and straightforward, the book describes the emergence of rather intricate behavior, provoking the interest of readers for further developments and applications of related topics.
Uncertainty Analysis for Engineers and Scientists
Build the skills for determining appropriate error limits for quantities that matter with this essential toolkit. Understand how to handle a complete project and how uncertainty enters into various steps. Provides a systematic, worksheet-based process to determine error limits on measured quantities, and all likely sources of uncertainty are explored, measured or estimated. Features instructions on how to carry out error analysis using Excel and MATLAB(R), making previously tedious calculations easy. Whether you are new to the sciences or an experienced engineer, this useful resource provides a practical approach to performing error analysis. Suitable as a text for a junior or senior level laboratory course in aerospace, chemical and mechanical engineering, and for professionals.
Uncertainty Analysis for Engineers and Scientists
Build the skills for determining appropriate error limits for quantities that matter with this essential toolkit. Understand how to handle a complete project and how uncertainty enters into various steps. Provides a systematic, worksheet-based process to determine error limits on measured quantities, and all likely sources of uncertainty are explored, measured or estimated. Features instructions on how to carry out error analysis using Excel and MATLAB(R), making previously tedious calculations easy. Whether you are new to the sciences or an experienced engineer, this useful resource provides a practical approach to performing error analysis. Suitable as a text for a junior or senior level laboratory course in aerospace, chemical and mechanical engineering, and for professionals.
Nonlinear Dynamics, Chaos, and Complexity
Chapter 1. Professor Valentin Afraimovich by Alexandra Afraimovich Chapter 2.The need for more integration between machine learning and neuroscience by Adrian Hernandez, Jose M. Amigo Chapter 3.Quasiperiodic Route to Transient Chaos in Vibroimpact System by Victor Bazhenov, Olga Pogorelova, Tatiana Postnikova Chapter 4. Modeling Ensembles of Nonlinear Dynamic Systems in Ultrawideb and Active Wireless Direct Chaotic Networks by A.S. Dmitriev, R.Yu. Yemelyanov, M.Yu. Gerasimov, Yu.V. Andreyev Chapter 5.Verification of Biomedical Processes with Anomalous Diffusion, Transport and Interaction of Species by Messoud Efendiev, Vitali Vougalter Chapter6.Chaos-based communication using isochronal synchronization: considerations about the synchronization manifold byJ.M.V. Grzybowski, E.E.N. Macau, T. Yoneyama Chapter 7.A sequential order of periodic motions in a 1-dimensional, time-delay, dynamical system by Siyuan Xing and Albert C. J. Luo Chapter 8.On the Geometric Approach to Transformations of the Coordinates of Inertial Frames of Reference by A.A. Talyshev Chapter 9.Corpuscular models of information transfer in a random environment by V.V. Uchaikin Chapter 10. Kinetic equation for systems with resonant captures and scatterings by A.V. Artemyev, A.I. Neishtadt, A.A. Vasiliev Chapter 11. Solvability In The Sense Of Sequences For Some Non-Fredholm Operators In Higher Dimensions by Vitali Vougalter, Vitaly Volpert
Examples and Problems in Advanced Calculus: Real-Valued Functions
This book includes over 500 most challenging exercises and problems in calculus. Topical problems and exercises are discussed on set theory, numbers, functions, limits and continuity, derivative, integral calculus, Rolle's theorem, mean value theorem, optimization problems, sequences and series. All the seven chapters recall important definitions, theorems and concepts, making this book immensely valuable to undergraduate students of engineering, mathematics, statistics, computer science and basic sciences.
Project-Based R Companion to Introductory Statistics
This book is envisioned as companion to a traditional statistics or biostatistics textbook, with each chapter covering usual topics such as descriptive statistics, regression, and hypothesis testing. However, each chapter will present its material using a complete step-by-step analysis of a real publicly-available dataset.
Reliability Calculations with the Stochastic Finite Element
Reliability Calculations with the Stochastic Finite Element presents different methods of reliability analysis for systems. Chapters explain methods used to analyze a number of systems such as single component maintenance system, repairable series system, rigid rotor balance, spring mechanics, gearbox design and optimization, and nonlinear vibration. The author proposes several established and new methods to solve reliability problems which are based on fuzzy systems, sensitivity analysis, Monte Carlo simulation, HL-RF methods, differential equations, and stochastic finite element processing, to name a few.This handbook is a useful update on reliability analysis for mechanical engineers and technical apprentices.
Modal View of Atmospheric Variability
This book reviews the theory and applications of the normal-mode functions in numerical weather prediction and weather and climate dynamics. The normal-mode functions, the eigensolutions of the linearized primitive equations describing the evolution of atmospheric winds and mass variables, have been used for a long time. They have played an important role in the development of data assimilation schemes and the initialization of numerical weather prediction models. Chapters also present how the normal modes can be applied to many theoretical and numerical problems in the atmospheric sciences, such as equatorial wave dynamics, baroclinic instability, energy transfers, and predictability across scales.
Statistical Analysis of Graph Structures in Random Variable Networks
This book studies complex systems with elements represented by random variables. Its main goal is to study and compare uncertainty of algorithms of network structure identification with applications to market network analysis. For this, a mathematical model of random variable network is introduced, uncertainty of identification procedure is defined through a risk function, random variables networks with different measures of similarity (dependence) are discussed, and general statistical properties of identification algorithms are studied. The volume also introduces a new class of identification algorithms based on a new measure of similarity and prove its robustness in a large class of distributions, and presents applications to social networks, power transmission grids, telecommunication networks, stock market networks, and brain networks through a theoretical analysis that identifies network structures. Both researchers and graduate students in computer science, mathematics, and optimization will find the applications and techniques presented useful.
Substitution and Tiling Dynamics: Introduction to Self-Inducing Structures
Delone sets and dynamical systems.- Introduction to hierarchical tiling dynamical systems.- S-adic sequences: dynamics, arithmetic, and geometry.- Operators and Algebras for Aperiodic Tilings.- From games to morphisms.- The Undecidability of the Domino Problem.- Renormalisation for block substitutions.- Yet another characterization of the Pisot conjecture.
New Trends in Applied Harmonic Analysis, Volume 2
This contributed volume collects papers based on courses and talks given at the 2017 CIMPA school Harmonic Analysis, Geometric Measure Theory and Applications, which took place at the University of Buenos Aires in August 2017. These articles highlight recent breakthroughs in both harmonic analysis and geometric measure theory, particularly focusing on their impact on image and signal processing. The wide range of expertise present in these articles will help readers contextualize how these breakthroughs have been instrumental in resolving deep theoretical problems. Some topics covered include: Gabor framesFalconer distance problemHausdorff dimensionSparse inequalitiesFractional Brownian motionFourier analysis in geometric measure theoryThis volume is ideal for applied and pure mathematicians interested in the areas of image and signal processing. Electrical engineers and statisticians studying these fields will also find this to be a valuable resource.
Advanced Topics in Mathematical Analysis
This edited book is aimed at researchers, graduate students, educators and engineers with interest in mathematics in general, and in mathematical analysis in particular. The book aims to present theory, methods, and applications of the selected topics that have recent research importance and use.
Entrepreneurial Complexity
This book deals with theoretical and practical results of Entrepreneurial Sciences and Management (ESM), emphasising quantitative methods. ESM has been a modern and exciting research field in which methods from various disciplines have been applied.
Time-Fractional Differential Equations
This book aims to establish a foundation for fractional derivatives and fractional differential equations. The theory of fractional derivatives enables considering any positive order of differentiation. The history of research in this field is very long, with its origins dating back to Leibniz. Since then, many great mathematicians, such as Abel, have made contributions that cover not only theoretical aspects but also physical applications of fractional calculus. The fractional partial differential equations govern phenomena depending both on spatial and time variables and require more subtle treatments. Moreover, fractional partial differential equations are highly demanded model equations for solving real-world problems such as the anomalous diffusion in heterogeneous media. The studies of fractional partial differential equations have continued to expand explosively. However we observe that available mathematical theory for fractional partial differential equations is not still complete. In particular, operator-theoretical approaches are indispensable for some generalized categories of solutions such as weak solutions, but feasible operator-theoretic foundations for wide applications are not available in monographs.To make this monograph more readable, we are restricting it to a few fundamental types of time-fractional partial differential equations, forgoing many other important and exciting topics such as stability for nonlinear problems. However, we believe that this book works well as an introduction to mathematical research in such vast fields.
Inequalities in Analysis and Probability (Third Edition)
The book introduces classical inequalities in vector and functional spaces with applications to probability. It develops new analytical inequalities, with sharper bounds and generalizations to the sum or the supremum of random variables, to martingales, to transformed Brownian motions and diffusions, to Markov and point processes, renewal, branching and shock processes.In this third edition, the inequalities for martingales are presented in two chapters for discrete and time-continuous local martingales with new results for the bound of the norms of a martingale by the norms of the predictable processes of its quadratic variations, for the norms of their supremum and their p-variations. More inequalities are also covered for the tail probabilities of Gaussian processes and for spatial processes.This book is well-suited for undergraduate and graduate students as well as researchers in theoretical and applied mathematics.
Mathematics (Education) in the Information Age
This book brings together ideas from experts in cognitive science, mathematics, and mathematics education to discuss these issues and to present research on how mathematics and its learning and teaching are evolving in the Information Age. Given the ever-broadening trends in Artificial Intelligence and the processing of information generally, the aim is to assess their implications for how math is evolving and how math should now be taught to a generation that has been reared in the Information Age. It will also look at the ever-spreading assumption that human intelligence may not be unique--an idea that dovetails with current philosophies of mind such as posthumanism and transhumanism. The role of technology in human evolution has become critical in the contemporary world. Therefore, a subgoal of this book is to illuminate how humans now use their sophisticated technologies to chart cognitive and social progress. Given the interdisciplinary nature of the chapters, this will be of interest to all kinds of readers, from mathematicians themselves working increasingly with computer scientists, to cognitive scientists who carry out research on mathematics cognition and teachers of mathematics in a classroom.
Data Science
Tap into the power of data science with this comprehensive resource for non-technical professionals Data Science: The Executive Summary - A Technical Book for Non-Technical Professionals is a comprehensive resource for people in non-engineer roles who want to fully understand data science and analytics concepts. Accomplished data scientist and author Field Cady describes both the "business side" of data science, including what problems it solves and how it fits into an organization, and the technical side, including analytical techniques and key technologies. Data Science: The Executive Summary covers topics like: Assessing whether your organization needs data scientists, and what to look for when hiring them When Big Data is the best approach to use for a project, and when it actually ties analysts' hands Cutting edge Artificial Intelligence, as well as classical approaches that work better for many problems How many techniques rely on dubious mathematical idealizations, and when you can work around them Perfect for executives who make critical decisions based on data science and analytics, as well as mangers who hire and assess the work of data scientists, Data Science: The Executive Summary also belongs on the bookshelves of salespeople and marketers who need to explain what a data analytics product does. Finally, data scientists themselves will improve their technical work with insights into the goals and constraints of the business situation.
Frontiers of Dynamic Games
This book includes papers presented at the ISDG12-GTM2019 International Meeting on Game Theory, as a joint meeting of the 12th International ISDG Workshop and the 13th "International Conference on Game Theory and Management", held in St. Petersburg in July 2019.The topics cover a wide range of game-theoretic models and include both theory and applications, including applications to management.
