Excel 2019 for Environmental Sciences Statistics
This book shows the capabilities of Microsoft Excel in teaching environmental science statistics effectively. Similar to the previously published Excel 2016 for Environmental Sciences Statistics, this book is a step-by-step, exercise-driven guide for students and practitioners who need to master Excel to solve practical environmental science problems. If understanding statistics isn't the reader's strongest suit, the reader is not mathematically inclined, or if the reader is new to computers or to Excel, this is the book to start off with.Excel, a widely available computer program for students and managers, is also an effective teaching and learning tool for quantitative analyses in environmental science courses. Its powerful computational ability and graphical functions make learning statistics much easier than in years past. Excel 2019 for Environmental Sciences Statistics: A Guide to Solving Practical Problems capitalizes on these improvements by teaching students and managers how to apply Excel to statistical techniques necessary in their courses and work.In this new edition, each chapter explains statistical formulas and directs the reader to use Excel commands to solve specific, easy-to-understand environmental science problems. Practice problems are provided at the end of each chapter with their solutions in an appendix. Separately, there is a full practice test (with answers in an appendix) that allows readers to test what they have learned.
Statistical Regression Modeling with R
This book provides a concise point of reference for the most commonly used regression methods. It begins with linear and nonlinear regression for normally distributed data, logistic regression for binomially distributed data, and Poisson regression and negative-binomial regression for count data. It then progresses to these regression models that work with longitudinal and multi-level data structures. The volume is designed to guide the transition from classical to more advanced regression modeling, as well as to contribute to the rapid development of statistics and data science. With data and computing programs available to facilitate readers' learning experience, Statistical Regression Modeling promotes the applications of R in linear, nonlinear, longitudinal and multi-level regression. All included datasets, as well as the associated R program in packages nlme and lme4 for multi-level regression, are detailed in Appendix A. This book will be valuable in graduate courses on applied regression, as well as for practitioners and researchers in the fields of data science, statistical analytics, public health, and related fields.
Control of Degenerate and Singular Parabolic Equations
This book collects some basic results on the null controllability for degenerate and singular parabolic problems. It aims to provide postgraduate students and senior researchers with a useful text, where they can find the desired statements and the related bibliography. For these reasons, the authors will not give all the detailed proofs of the given theorems, but just some of them, in order to show the underlying strategy in this area.
Bayesian Inference of State Space Models
Bayesian Inference of State Space Models: Kalman Filtering and Beyond offers a comprehensive introduction to Bayesian estimation and forecasting for state space models. The celebrated Kalman filter, with its numerous extensions, takes centre stage in the book. Univariate and multivariate models, linear Gaussian, non-linear and non-Gaussian models are discussed with applications to signal processing, environmetrics, economics and systems engineering. Over the past years there has been a growing literature on Bayesian inference of state space models, focusing on multivariate models as well as on non-linear and non-Gaussian models. The availability of time series data in many fields of science and industry on the one hand, and the development of low-cost computational capabilities on the other, have resulted in a wealth of statistical methods aimed at parameter estimation and forecasting. This book brings together many of these methods, presenting an accessible and comprehensive introduction to state space models. A number of data sets from different disciplines are used to illustrate the methods and show how they are applied in practice. The R package BTSA, created for the book, includes many of the algorithms and examples presented. The book is essentially self-contained and includes a chapter summarising the prerequisites in undergraduate linear algebra, probability and statistics. An up-to-date and complete account of state space methods, illustrated by real-life data sets and R code, this textbook will appeal to a wide range of students and scientists, notably in the disciplines of statistics, systems engineering, signal processing, data science, finance and econometrics. With numerous exercises in each chapter, and prerequisite knowledge conveniently recalled, it is suitable for upper undergraduate and graduate courses.
Numerical Simulation in Physics and Engineering: Trends and Applications
This book results from the XVIII Spanish-French School 'Jacques Louis Lions' on Numerical Simulation in Physics and Engineering, that took place in Las Palmas de Gran Canaria from 25th to 29th June 2018. These conferences are held biennially since 1984 and sponsored by the Spanish Society of Applied Mathematics (SEMA). They also have the sponsorship of the Soci矇t矇 de Math矇matiques Appliqu矇es et Industrielles (SMAI) of France since 2008. Each edition is organized around several main courses and talks delivered by renowned French/Spanish scientists. This volume is highly recommended to graduate students in Engineering or Science who want to focus on numerical simulation, either as a research topic or in the field of industrial applications. It can also benefit senior researchers and technicians working in industry who are interested in the use of state-of-the-art numerical techniques. Moreover, the book can be used as a textbook for master courses in Mathematics, Physics, or Engineering.
Faces of Geometry
The volume reports on interdisciplinary discussions and interactions between theoretical research and practical studies on geometric structures and their applications in architecture, the arts, design, education, engineering, and mathematics. These related fields of research can enrich each other and renew their mutual interest in these topics through networks of shared inspiration, and can ultimately enhance the quality of geometry and graphics education. Particular attention is dedicated to the contributions that women have made to the scientific community and especially mathematics. The book introduces engineers, architects and designers interested in computer applications, graphics and geometry to the latest advances in the field, with a particular focus on science, the arts and mathematics education.
Big Data Analytics for Internet of Things
BIG DATA ANALYTICS FOR INTERNET OF THINGS Discover the latest developments in IoT Big Data with a new resource from established and emerging leaders in the fieldBig Data Analytics for Internet of Things delivers a comprehensive overview of all aspects of big data analytics in Internet of Things (IoT) systems. The book includes discussions of the enabling technologies of IoT data analytics, types of IoT data analytics, challenges in IoT data analytics, demand for IoT data analytics, computing platforms, analytical tools, privacy, and security.The distinguished editors have included resources that address key techniques in the analysis of IoT data. The book demonstrates how to select the appropriate techniques to unearth valuable insights from IoT data and offers novel designs for IoT systems.With an abiding focus on practical strategies with concrete applications for data analysts and IoT professionals, Big Data Analytics for Internet of Things also offers readers: A thorough introduction to the Internet of Things, including IoT architectures, enabling technologies, and applicationsAn exploration of the intersection between the Internet of Things and Big Data, including IoT as a source of Big Data, the unique characteristics of IoT data, etc.A discussion of the IoT data analytics, including the data analytical requirements of IoT data and the types of IoT analytics, including predictive, descriptive, and prescriptive analyticsA treatment of machine learning techniques for IoT data analyticsPerfect for professionals, industry practitioners, and researchers engaged in big data analytics related to IoT systems, Big Data Analytics for Internet of Things will also earn a place in the libraries of IoT designers and manufacturers interested in facilitating the efficient implementation of data analytics strategies.
Analytic and Probabilistic Approaches to Dynamics in Negative Curvature
The work consists of two introductory courses, developing different points of view on the study of the asymptotic behaviour of the geodesic flow, namely: the probabilistic approach via martingales and mixing (by St矇phane Le Borgne); the semi-classical approach, by operator theory and resonances (by Fr矇d矇ric Faure and Masato Tsujii). The contributions aim to give a self-contained introduction to the ideas behind the three different approaches to the investigation of hyperbolic dynamics. The first contribution focus on the convergence towards a Gaussian law of suitably normalized ergodic sums (Central Limit Theorem). The second one deals with Transfer Operators and the structure of their spectrum (Ruelle-Pollicott resonances), explaining the relation with the asymptotics of time correlation function and the periodic orbits of the dynamics.
Stochastic Communities
The book presents a novel theory of bioversity by analyzing the distribution of abundances among species in the context of a community. The basis of this new theory is a distribution called the "J distribution."
Asymptotic Theory of Dynamic Boundary Value Problems in Irregular Domains
This book considers dynamic boundary value problems in domains with singularities of two types. The first type consists of "edges" of various dimensions on the boundary; in particular, polygons, cones, lenses, polyhedra are domains of this type. Singularities of the second type are "singularly perturbed edges" such as smoothed corners and edges and small holes. A domain with singularities of such type depends on a small parameter, whereas the boundary of the limit domain (as the parameter tends to zero) has usual edges, i.e. singularities of the first type. In the transition from the limit domain to the perturbed one, the boundary near a conical point or an edge becomes smooth, isolated singular points become small cavities, and so on. In an "irregular" domain with such singularities, problems of elastodynamics, electrodynamics and some other dynamic problems are discussed. The purpose is to describe the asymptotics of solutions near singularities of the boundary. The presented results and methods have a wide range of applications in mathematical physics and engineering. The book is addressed to specialists in mathematical physics, partial differential equations, and asymptotic methods.
Systems Immunology
This book provides a complete overview of computational immunology, from basic concepts to mathematical modeling at the single molecule, cellular, organism, and population levels. It showcases modern mechanistic models and their use in making predictions, designing experiments, and elucidating underlying biochemical processes.
Iterative Methods and Their Dynamics with Applications
In this book you can find theory and applications of classical and new iterative root-finding algorithms and families of iterative methods. Some recently discovered graphical tools are presented, studied, and used in order to find the best methods in convergence terms. Moreover, the differences between real and complex behaviors are presented. F
Theory of Stabilization for Linear Boundary Control Systems
This book presents a unified algebraic approach to stabilization problems of linear boundary control systems with no assumption on finite-dimensional approximations to the original systems, such as the existence of the associated Riesz basis. A new proof of the stabilization result for linear systems of finite dimension is also presented, leadin
A Complete Solution Guide to Real and Complex Analysis II
This is a complete solution guide to all exercises from Chapters 10 to 20 in Rudin's Real and Complex Analysis. The features of this book are as follows: It covers all the 221 exercises from Chapters 10 to 20 with detailed and complete solutions. As a matter of fact, my solutions show every detail, every step and every theorem that I applied. There are 29 illustrations for explaining the mathematical concepts or ideas used behind the questions or theorems. Sections in each chapter are added so as to increase the readability of the exercises. Different colors are used frequently in order to highlight or explain problems, lemmas, remarks, main points/formulas involved, or show the steps of manipulation in some complicated proofs. (ebook only) Necessary lemmas with proofs are provided because some questions require additional mathematical concepts which are not covered by Rudin. Many useful or relevant references are provided to some questions for your future research.
Sturge’s Statistical and Thermal Physics, Second Edition
This fully revised and updated edition provides a uniquely accessible introduction to the principles and applications of statistical mechanics and thermodynamics. Based on the highly acclaimed text by famous physicist M.D. Sturge, it continues its emphasis on explaining concepts with simple mathematics and plain English.
Applied Epidemiologic Principles and Concepts
This book provides practical knowledge to clinicians and biomedical researchers using biological and biochemical specimen in order to understand health and disease processes at cellular, clinical, and population levels. Concepts and techniques provided will help researchers design and conduct studies, then translate data from bench to clinics.
Bird’s Higher Engineering Mathematics
Higher Engineering Mathematics has helped thousands of students to succeed in their exams by developing problem-solving skills, It is supported by over 600 practical engineering examples and applications which relate theory to practice. The extensive and thorough topic coverage makes this a solid text for undergraduate and upper-level vocational courses. Its companion website provides resources for both students and lecturers, including lists of essential formulae, ands full solutions to all 2,000 further questions contained in the 277 practice exercises; and illustrations and answers to revision tests for adopting course instructors.
Bird's Higher Engineering Mathematics
Higher Engineering Mathematics has helped thousands of students to succeed in their exams by developing problem-solving skills, It is supported by over 600 practical engineering examples and applications which relate theory to practice. The extensive and thorough topic coverage makes this a solid text for undergraduate and upper-level vocational courses. Its companion website provides resources for both students and lecturers, including lists of essential formulae, ands full solutions to all 2,000 further questions contained in the 277 practice exercises; and illustrations and answers to revision tests for adopting course instructors.
Nonlinear Evolution and Difference Equations of Monotone Type in Hilbert Spaces
This book deals with first and second order evolution and difference monotone type equations. The approach followed in the book was first introduced by Dr. Djafari-Rouhani, and later advanced by him along with Dr. Khatibzadeh.
Analysis and Control of Finite-Value Systems
A comprehensive work in finite-value systems that covers the latest achievements using the semi-tensor product method, on various kinds of finite-value systems. The book contains examples to provide a better understanding of the practical applications of finite-value systems.
Understanding Digital Signal Processing with Matlab(r) and Solutions
The book discusses signals that most electrical engineers detect and study. The vast majority of signals could never be detected due to random additive signals, known as noise, that distorts them or completely overshadows them. The text presents the methods for extracting the desired signals from the noise. It includes examples that use MATLAB.
Metamodeling for Variable Annuities
This book is devoted to the mathematical methods of metamodeling that can be used to speed up the valuation of large portfolios of variable annuities. It is suitable for advanced undergraduate students, graduate students, and practitioners.
Mathematics Applied to Engineering and Management
This book offers the latest research advances in the field of mathematics applications in engineering sciences and provides a reference with a theoretical and sound background, along with case studies.
Mathematics in Engineering Sciences
The aim is to publish the research studies, novel theory, as well as new methodology and applications in mathematics and management sciences. It will provide a comprehensive range of mathematics applied in engineering areas for different tasks. It will offer an international perspective and a bridge between classical theory and new methodology.
Modeling and Computing for Geotechnical Engineering
This book introduces three phases involved in the modeling and computing of engineered systems: Idealization of the actual physical problem, Formulation of a mathematical model represented by a set of equations governing the response of the system, and Solution of the governing equations and graphical representation of the numerical results
Concise Introduction to Basic Real Analysis
This concise book includes all basic and essential topics of Real Analysis, for the first time learner. It is for those that are involved with Real Analysis in disciplines such as engineering, technology, and other physical sciences.
Economic Evaluation of Cancer Drugs
The first book on the design and analysis of not only clinical trials but also how observational non-interventional data using clinical data is applied to economic evaluation and re-imbursement in the context of Cancer. This book is a non technical exposition of economic evaluation and no knowledge of advanced statistical methods is assumed.
Bioequivalence and Statistics in Clinical Pharmacology
Maintaining a practical perspective, Bioequivalence and Statistics in Clinical Pharmacology, Second Edition explores statistics used in day-to-day clinical pharmacology work. The book is a starting point for those involved in such research and covers the methods needed to design, analyze, and interpret bioequivalence trials; explor
Robust Methods for Data Reduction
This book gives a non-technical overview of robust data reduction techniques, encouraging the use of these important and useful methods in practical applications. The main areas covered include principal components analysis, sparse principal component analysis, canonical correlation analysis, factor analysis, clustering, double clustering, and d
Big Data Analysis for Bioinformatics and Biomedical Discoveries
This book is a practical guide to the nuts and bolts of Big Data, enabling readers to quickly and effectively harness the power of Big Data to make groundbreaking biological discoveries, carry out translational medical research, and implement personalized genomic medicine. Contributing to the NIH Big Data to Knowledge (BD2K) initiative, the book
Crop Breeding
This title includes a number of Open Access chapters. Climate change will severely impact the world's food supply unless steps are taken to increase crop resilience. Otherwise, the negative effects on both the yield and the quality of crop plants are predicted to be immense. Plant genomics is a potentially powerful defense against this looming threat. This compendium volume offers a global perspective on the topic, with contributions from 42 eminent researchers from 12 nations around the world. The editor is a respected and published scientist in the bioinformatics field, who has chosen articles in the following topics: An overview of the genetic challenges presented by climate changeA genomic toolkit for crop-related researchSpecific methods of improvement for specific crop by means of genomic applicationsThe hand-picked up-to-date research makes this volume an excellent reference not only for university-level academics, but also for policymakers and stakeholders who must tackle the challenge of the world's food security.
Differential Equations
This book takes a problem solving approach in displaying equations, giving explanations, and how to plot with minimal input. Matlab Symbolic toolbox makes it possible to get differential equations, analytical expressions, solutions, plots, etc. in a format that replicates an instructor's classwork.
Bayesian Disease Mapping
Since the publication of the second edition, many new Bayesian tools and methods have been developed for space-time data analysis, the predictive modeling of health outcomes, and other spatial biostatistical areas. Exploring these new developments, the third edition provides an up-to-date, cohesive account of the full range of Bayesian disease m
Power Analysis of Trials with Multilevel Data
Power Analysis of Trials with Multilevel Data is a valuable reference for anyone who wants to perform power calculations on trials with hierarchical data. It provides a thorough overview of power analysis, familiarizing you with terminology and notation, outlining the key concepts of statistical power and power analysis, and cov
Scientific Computing with Matlab(r)
Improving students' ability to tackle mathematical problems, this second edition retains the structure of its predecessor while expanding and updating the content of each chapter.
Introduction to Mathematical Oncology
Extensively classroom-tested in undergraduate and graduate courses, this self-contained book presents biologically well-motivated and mathematically tractable models that facilitate both a deep understanding of cancer biology and better cancer treatment designs. It covers the medical and biological background of the diseases, modeling issues, an
Grid-Based Nonlinear Estimation and Its Applications
Featuring a unified framework to derive different grid-based nonlinear estimation algorithms from a numerical integration perspective, this book discusses the fundamental concepts of many widely used nonlinear estimation techniques.
Mathematical and Statistical Skills in the Biopharmaceutical Industry
Discusses integral, pragmatic approach to solving problems relevant to biostatistics function in the pharmaceutical industry, emphasizes importance of logical, systematic thinking, clear problem formulation and answering research questions in selected terms.
Hidden Markov Models
It presents analysis of both continuous and discrete Markov chains. It deals with concepts in a generic way, most books on Hidden Markov Models focus on speech processing applications. It presents the translation of Hidden Markov Models concepts from the realm of formal mathematics into computer codes using a high-level language.
Applied Statistical Inference with Minitab(r)
Covers material typically presented in an intermediate statistics course at the undergraduate level and a first course in applied statistics at the graduate level. Topics include basic statistical inference, regression, and ANOVA. Advanced topics include non-parametric statistics, logistic regression, and goodness-of-fit tests.
Mathematical Models of Plant-Herbivore Interactions
This book addresses mathematical models in the study of practical questions in ecology, particularly factors that affect herbivory. It will be of use for graduate students and researchers interested in mathematical biology and ecology.
Advanced Mathematical Techniques in Engineering Sciences
Mathematical techniques are the strength of engineering sciences and form the common foundation of all novel discipline as engineering sciences. The book Advanced Mathematical Techniques in Engineering Sciences involved in an ample range of mathematical tools and techniques applied in various fields of engineering sciences. Through this book the
Bayesian Analysis of Time Series
This book will describe how to use models that explain the probabilistic characteristics of a time series while the Bayesian approach will provide inferences about those probabilistic characteristics.
Finite Element Analysis
This book provides an introduction to finite element analysis as a tool for the solution of practical engineering problems; teach the principles of finite element analysis including the mathematical fundamentals as required; to how to construct an appropriate finite element model of a physical system, to interpret the results of the analysis.
Pyomo -- Optimization Modeling in Python
This book provides a complete and comprehensive guide to Pyomo (Python Optimization Modeling Objects) for beginning and advanced modelers, including students at the undergraduate and graduate levels, academic researchers, and practitioners. Using many examples to illustrate the different techniques useful for formulating models, this text beautifully elucidates the breadth of modeling capabilities that are supported by Pyomo and its handling of complex real-world applications. In the third edition, much of the material has been reorganized, new examples have been added, and a new chapter has been added describing how modelers can improve the performance of their models. The authors have also modified their recommended method for importing Pyomo. A big change in this edition is the emphasis of concrete models, which provide fewer restrictions on the specification and use of Pyomo models. Pyomo is an open source software package for formulating and solving large-scale optimization problems. The software extends the modeling approach supported by modern AML (Algebraic Modeling Language) tools. Pyomo is a flexible, extensible, and portable AML that is embedded in Python, a full-featured scripting language. Python is a powerful and dynamic programming language that has a very clear, readable syntax and intuitive object orientation. Pyomo includes Python classes for defining sparse sets, parameters, and variables, which can be used to formulate algebraic expressions that define objectives and constraints. Moreover, Pyomo can be used from a command-line interface and within Python's interactive command environment, which makes it easy to create Pyomo models, apply a variety of optimizers, and examine solutions.
A Derivative-Free Two Level Random Search Method for Unconstrained Optimization
The book is intended for graduate students and researchers in mathematics, computer science, and operational research. The book presents a new derivative-free optimization method/algorithm based on randomly generated trial points in specified domains and where the best ones are selected at each iteration by using a number of rules. This method is different from many other well established methods presented in the literature and proves to be competitive for solving many unconstrained optimization problems with different structures and complexities, with a relative large number of variables. Intensive numerical experiments with 140 unconstrained optimization problems, with up to 500 variables, have shown that this approach is efficient and robust. Structured into 4 chapters, Chapter 1 is introductory. Chapter 2 is dedicated to presenting a two level derivative-free random search method for unconstrained optimization. It is assumed that the minimizing function is continuous, lower bounded and its minimum value is known. Chapter 3 proves the convergence of the algorithm. In Chapter 4, the numerical performances of the algorithm are shown for solving 140 unconstrained optimization problems, out of which 16 are real applications. This shows that the optimization process has two phases: the reduction phase and the stalling one. Finally, the performances of the algorithm for solving a number of 30 large-scale unconstrained optimization problems up to 500 variables are presented. These numerical results show that this approach based on the two level random search method for unconstrained optimization is able to solve a large diversity of problems with different structures and complexities. There are a number of open problems which refer to the following aspects: the selection of the number of trial or the number of the local trial points, the selection of the bounds of the domains where the trial points and the local trial points are randomly generated and a criterion for initiating the line search.
Asymptotic Properties of Permanental Sequences
This SpringerBriefs employs a novel approach to obtain the precise asymptotic behavior at infinity of a large class of permanental sequences related to birth and death processes and autoregressive Gaussian sequences using techniques from the theory of Gaussian processes and Markov chains. The authors study alpha-permanental processes that are positive infinitely divisible processes determined by the potential density of a transient Markov process. When the Markov process is symmetric, a 1/2-permanental process is the square of a Gaussian process. Permanental processes are related by the Dynkin isomorphism theorem to the total accumulated local time of the Markov process when the potential density is symmetric, and by a generalization of the Dynkin theorem by Eisenbaum and Kaspi without requiring symmetry. Permanental processes are also related to chi square processes and loop soups. The book appeals to researchers and advanced graduate students interested in stochastic processes, infinitely divisible processes and Markov chains.
From Operator Theory to Orthogonal Polynomials, Combinatorics, and Number Theory
The main topics of this volume, dedicated to Lance Littlejohn, are operator and spectral theory, orthogonal polynomials, combinatorics, number theory, and the various interplays of these subjects. Although the event, originally scheduled as the Baylor Analysis Fest, had to be postponed due to the pandemic, scholars from around the globe have contributed research in a broad range of mathematical fields. The collection will be of interest to both graduate students and professional mathematicians.Contributors are: G.E. Andrews, B.M. Brown, D. Damanik, M.L. Dawsey, W.D. Evans, J. Fillman, D. Frymark, A.G. Garc穩a, L.G. Garza, F. Gesztesy, D. G籀mez-Ullate, Y. Grandati, F.A. Gr羹nbaum, S. Guo, M. Hunziker, A. Iserles, T.F. Jones, K. Kirsten, Y. Lee, C. Liaw, F. Marcell獺n, C. Markett, A. Martinez-Finkelshtein, D. McCarthy, R. Milson, D. Mitrea, I. Mitrea, M. Mitrea, G. Novello, D. Ong, K. Ono, J.L. Padgett, M.M.M. Pang, T. Poe, A.Sri Ranga, K. Schiefermayr, Q. Sheng, B. Simanek, J. Stanfill, L. Vel獺zquez, M. Webb, J. Wilkening, I.G. Wood, M. Zinchenko.
