Thorough presentation of the problem of portfolio optimization, leading in a natural way to the Capital Market Theory Dynamic programming and the optimal portfolio selection-consumption problem through time An intuitive approach to Brownian motion and stochastic integral models for continuous time problems The Black-Scholes equation for simple European option values, derived in several different ways A chapter on several types of exotic options and one on material on the management of risk in several contexts

Towards Inclusive Societies: Psychological and Sociological Perspectives focuses on the importance of building inclusive societies and communities for global human welfare within psychological, social, political, and cultural realms. It discusses the engagement of psychology and other social science disciplines on the need for building both cultural sensitivity and interdisciplinary dialogue. The volume presents the issues and consequences of globalization and diversity in the social and psychological domains and their role in shaping the physical and mental health of people. It systematically examines the various parameters of inclusivity such as equality, equity, social identity, social stigma, and coexistence of differences in socio-cultural behaviour. The volume focuses on the developments towards building inclusive societies in the South Asian countries including, India, Bangladesh, and Nepal. It also highlights the challenges and possibilities in making social-psychological discourses more inclusive. This book will be of interest to students, teachers, and scholars of psychology, cultural psychology, gender psychology, social psychology, sociology, and political science and social work. It will also be useful for psychologists, sociologists, social scientists, social workers, political scientists, and Gandhian philosophers.

Contents:
Introduction. Acoustical Oceanography. Propagation I. Observations and Physical Models. Propagation II. Mathematical Models (Part One). Propagation II. Mathematical Models (Part Two). Noise I. Observations and Physical Models. Noise II. Mathematical Models. Reverberation I. Observations and Physical Models. Reverberation II. Observations and Physical Models. Sonar Performance Models. Model Evaluation. Simulation.

The most useful tool for reviewing mathematical methods for economics classes-now with more content Schaum's Outline of Calculus for Business, Economics and Finance, Fourth Edition is the go-to study guide for help in economics courses, mirroring the courses in scope and sequence to help you understand basic concepts and get extra practice in topics like multivariable functions, exponential and logarithmic functions, and more. With an outline format that facilitates quick and easy review, Schaum's Outline of Calculus for Business, Economics and Finance, Fourth Edition supports the major bestselling textbooks in economics courses and is useful for a variety of classes, including Introduction to Economics, Economics, Econometrics, Microeconomics, Macroeconomics, Economics Theories, Mathematical Economics, Math for Economists and Math for Social Sciences. Chapters include Economic Applications of Graphs and Equations, The Derivative and the Rules of Differentiation, Calculus of Multivariable Functions, Exponential and Logarithmic Functions in Economics, Special Determinants and Matrices and Their Use in Economics, First-Order Differential Equations, and more. Features: NEW in this edition: Additional problems at the end of each chapter NEW in this edition: An additional chapter on sequences and series NEW in this edition: Two computer applications of Linear Programming in Excel 710 fully solved problems Outline format to provide a concise guide for study for standard college courses in mathematical economics Clear, concise explanations covers all course fundamentals Supplements the major bestselling textbooks in economics courses Appropriate for the following courses: Introduction to Economics, Economics, Econometrics, Microeconomics, Macroeconomics, Economics Theories, Mathematical Economics, Math for Economists, Math for Social Sciences

Exam Board: Pearson Edexcel Academic Level: AS level Subject: Mathematics First teaching: September 2017 First Exams: Summer 2018 This Revision Guide is suitable for classroom and independent study, and is the smart choice for those revising for AS Mathematics. Organise their revision with the one topic-per-page format Speed up their revision with summary notes in short, memorable chunks Track their revision progress with at-a-glance check boxes Check their understanding with worked examples Develop their exam technique with exam-style practice questions and answers

This book illustrates the current work of leading multilevel modeling (MLM) researchers from around the world.

The book's goal is to critically examine the real problems that occur when trying to use MLMs in applied research, such as power, experimental design, and model violations. This presentation of cutting-edge work and statistical innovations in multilevel modeling includes topics such as growth modeling, repeated measures analysis, nonlinear modeling, outlier detection, and meta analysis.

This volume will be beneficial for researchers with advanced statistical training and extensive experience in applying multilevel models, especially in the areas of education; clinical intervention; social, developmental and health psychology, and other behavioral sciences; or as a supplement for an introductory graduate-level course.

Spatial point processes play a fundamental role in spatial statistics and today they are a very active area of research with many new and emerging applications. Although published works address different aspects of spatial point processes, most of the classical literature deals only with nonparametric methods, and nowhere can one find a comprehensive treatment of the theory and applications of simulation-based inference. Written by researchers at the top of the field, this book collects and unifies recent theoretical advances and examples of applications. The authors examine Markov chain Monte Carlo (MCMC) algorithms and explore one of the most important recent developments in MCMC-perfect simulation procedures.

The MathFilm DVD presents a juried collection of innovative short math videos. The films are winners of the international competition of the MathFilm Festival 2008. Following the May premiere in Berlin, the festival films are shown in public viewings throughout Germany. The festival is part of the "Year of Mathematics" initiative of the Federal Ministry of Education and Research. The films target a broad audience of students, teachers, and everyone with an interest in mathematics. The topics range from geometry to graphics, from computing to visualization, from historic to modern achievements, from abstract mathematical worlds to real-world applications. The DVD provides entertaining and informative insights into modern mathematics and is an exciting resource for lively school and university courses.

Although the use of fuzzy control methods has grown nearly to the level of classical control, the true understanding of fuzzy control lags seriously behind. Moreover, most engineers are well versed in either traditional control or in fuzzy control-rarely both. Each has applications for which it is better suited, but without a good understanding of both, engineers cannot make a sound determination of which technique to use for a given situation.

A First Course in Fuzzy and Neural Control is designed to build the foundation needed to make those decisions. It begins with an introduction to standard control theory, then makes a smooth transition to complex problems that require innovative fuzzy, neural, and fuzzy-neural techniques. For each method, the authors clearly answer the questions: What is this new control method? Why is it needed? How is it implemented? Real-world examples, exercises, and ideas for student projects reinforce the concepts presented.

Developed from lecture notes for a highly successful course titled The Fundamentals of Soft Computing, the text is written in the same reader-friendly style as the authors' popular A First Course in Fuzzy Logic text. A First Course in Fuzzy and Neural Control requires only a basic background in mathematics and engineering and does not overwhelm students with unnecessary material but serves to motivate them toward more advanced studies.

This CGP Complete Revision & Practice book is a fantastic all-in-one guide to AS & A-Level Edexcel Further Maths (for courses starting in 2017 and beyond). It's bursting with crystal-clear revision notes and worked examples for the Core Pure topics as well as the Further Pure 1, Further Statistics 1, Further Mechanics 1 and Decision Mathematics 1 options. There are also plenty of exam-style questions to test students on what they've learned (including step-by-step answers at the back). And to top things off, the book comes with a free Online Edition - just use the code printed inside the book to read it on a PC, Mac or tablet.

This book contains a sampling of papers presented at the June 2-5, 2002 International Workshop on Bifurcations andamp; Instabilities in Geomechanics (IWBI 2002). The scope of the Workshop includes analytical approaches, numerical methods, and experimental techniques.

This book is written for the love of numbers. It tells their story, shows how they were invented and used to quantify our world, and explains what quantitative data mean for our lives. It aspires to contribute to overall numeracy through a tour de force presentation of the production, use, and evolution of data. Understanding our physical world, our economies, and our societies through quantification has been a persistent feature of human evolution. This book starts with a narrative on why and how our ancestors were driven to the invention of number, which is then traced to the eventual arrival at our number system. This is followed by a discussion of how numbers were used for counting, how they enabled the measurement of physical quantities, and how they led to the estimation of man-made and abstract notions in the socio-economic domain. As data don't fall like manna from the sky, a unique feature of this book is that it explains from a teacher's perspective how they're really conceived in our minds, how they're actually produced from individual observations, and how this defines their meaning and interpretation. It discusses the significance of standards, the use of taxonomies, and clarifies a series of misconceptions regarding the making of data. The book then describes the switch to a new research paradigm and its implications, highlights the arrival of microdata, illustrates analytical uses of data, and closes with a look at the future of data and our own role in it.

Updated and expanded, Bayesian Artificial Intelligence, Second Edition provides a practical and accessible introduction to the main concepts, foundation, and applications of Bayesian networks. It focuses on both the causal discovery of networks and Bayesian inference procedures. Adopting a causal interpretation of Bayesian networks, the authors discuss the use of Bayesian networks for causal modeling. They also draw on their own applied research to illustrate various applications of the technology. New to the Second Edition New chapter on Bayesian network classifiers New section on object-oriented Bayesian networks New section that addresses foundational problems with causal discovery and Markov blanket discovery New section that covers methods of evaluating causal discovery programs Discussions of many common modeling errors New applications and case studies More coverage on the uses of causal interventions to understand and reason with causal Bayesian networks Illustrated with real case studies, the second edition of this bestseller continues to cover the groundwork of Bayesian networks. It presents the elements of Bayesian network technology, automated causal discovery, and learning probabilities from data and shows how to employ these technologies to develop probabilistic expert systems. Web Resource The book's website at www.csse.monash.edu.au/bai/book/book.html offers a variety of supplemental materials, including example Bayesian networks and data sets. Instructors can email the authors for sample solutions to many of the problems in the text.

Examines flawed usage of math in public affairs through actual cases of how mathematical data and conclusions can be distorted and misrepresented to influence public opinion. Highlights how slippery numbers and questionable mathematical conlusions emerge and what can be done to safeguard against them. This pragmatic book examines flawed usage of math in public affairs through actual cases of how mathematical data and conclusions can be distorted and misrepresented to influence public opinion-highlighting how slippery numbers and questionable mathematical conclusions emerge and what can be done to safeguard against them. Gives specific examples of governmental and private sector math manipulation. Slippery Math in Public Affairs analyzes the cost of "slippery math" in terms of squandered resources identifies common misperceptions about the role of math in public affairs discusses how math education can be reformed to sharpen public awareness of "slippery math" offers exemplary self-study programs to improve perspective on the use of math depicts the development of math models and their use and misuse considers proper and improper polling methods With nearly 200 references cited, this book will benefit math teachers; educators; mathematicians; applied statisticians; multivariate analysts; biomathematicians and medical personnel; public administrators; political scientists; business administrators; operations managers; urban and public affairs officials; economists; demographers; sociologists; anthropologists; public-policy makers; public affairs analysts and commentators; journalists; and the general reader who seeks to avoid being manipulated by math; and is essential reading for undergraduate and graduate students in the aforementioned disciplines.

Population Genomics With R presents a multidisciplinary approach to the analysis of population genomics. The methods treated cover a large number of topics from traditional population genetics to large-scale genomics with high-throughput sequencing data. Several dozen R packages are examined and integrated to provide a coherent software environment with a wide range of computational, statistical, and graphical tools. Small examples are used to illustrate the basics and published data are used as case studies. Readers are expected to have a basic knowledge of biology, genetics, and statistical inference methods. Graduate students and post-doctorate researchers will find resources to analyze their population genetic and genomic data as well as help them design new studies. The first four chapters review the basics of population genomics, data acquisition, and the use of R to store and manipulate genomic data. Chapter 5 treats the exploration of genomic data, an important issue when analysing large data sets. The other five chapters cover linkage disequilibrium, population genomic structure, geographical structure, past demographic events, and natural selection. These chapters include supervised and unsupervised methods, admixture analysis, an in-depth treatment of multivariate methods, and advice on how to handle GIS data. The analysis of natural selection, a traditional issue in evolutionary biology, has known a revival with modern population genomic data. All chapters include exercises. Supplemental materials are available on-line (http://ape-package.ird.fr/PGR.html).

Thorough coverage, from the ground up, of tree-based methods (e.g., CART, conditional inference trees, bagging, boosting, and random forests). A companion website containing additional supplementary material and the code to reproduce every example and figure in the book. A companion R package, called treemisc, which contains several data sets and functions used throughout the book (e.g., there's an implementation of gradient tree boosting with LAD loss that shows how to perform the line search step by updating the terminal node estimates of a fitted rpart tree). Interesting examples that are of practical use; for example, how to construct partial dependence plots from a fitted model in Spark MLlib (using only Spark operations), or post-processing tree ensembles via the LASSO to reduce the number of trees while maintaining, or even improving performance.

When it comes to relationships, there's no shortage of advice from self-help 'experts', pick-up artists, and glossy magazines. But modern-day myths of attraction often have no basis in fact or - worse - are rooted in little more than misogyny. Based on science rather than self-help cliches, psychologist Viren Swami debunks these myths and draws on cutting-edge research to provide a ground-breaking and evidence-based account of relationship formation. At the core of this book is a very simple idea: there are no 'laws of attraction', no fool-proof methods or strategies for getting someone to date you. But this isn't to say that there's nothing to be gained from studying attraction. Based on science rather than self-help cliches, Attraction Explained looks at how factors such as geography, physical appearance, reciprocity, and similarity affect who we fall for and why. With updated statistics, this second edition also includes new content on online dating, queer relationships, racism in dating, shyness, and individual differences. It remains an engaging and accessible introduction to attraction relationship formation for professionals, students, and general readers.

Contains a compact disc with nearly 200 microcomputer programs illustrating a wide range of reliability and statistical analyses Mechanical Reliability Improvement provides probability and statistical concepts developed using pseudorandom numbers enumeration-, simulation-, and randomization-based statistical analyses for comparison of the test performance of alternative designs, as well as simulation- and randomization-based tests for examination of the credibility of statistical presumptions and discusses centroid and moment of inertia analogies for mean and variance the organization structure of completely randomized, randomized complete block, and split spot experiment test programs

First published in 2002. Routledge is an imprint of Taylor & Francis, an informa company.

This book will introduce digital humanists at all levels of education to Python. It provides background and guidance on learning the Python computer programming language, and as it presumes no knowledge on the part of the reader about computers or coding concepts allows the reader to gradually learn the more complex tasks that are currently popular in the field of digital humanities. This book will be aimed at undergraduates, graduates, and faculty who are interested in learning how to use Python as a tool within their workflow. An Introduction to Python for Digital Humanists will act as a primer for students who wish to use Python, allowing them to engage with more advanced textbooks. This book fills a real need, as it is first Python introduction to be aimed squarely at humanities students, as other books currently available do not approach Python from a humanities perspective. It will be designed so that those experienced in Python can teach from it, in addition to allowing those who are interested in being self-taught can use it for that purpose. Key Features: Data analysis Data science Computational humanities Digital humanities Python Natural language processing Social network analysis App development

Gear up and equip your organization for an entirely new competitive landscape In The Ecosystem Economy: How to Lead in the New Age of Sectors Without Borders, two McKinsey & Company senior partners offer an incisive and eye-opening look at the emerging ecosystem economy and what it means for companies used to familiar sector siloes. In the book, you'll explore how the most successful companies in the new economy aren't the ones that have applied old-school best practices but, instead, have adopted entirely new mindsets and approaches for a fundamentally transforming market. You'll also find: Explanations of why it's so important for companies to adopt a new approach in the face of a foundationally changing economy (and what they stand to gain) How the new ecosystem economy will continue to evolve and change, dissolving the borders between the traditional sectors of the economy A comprehensive ecosystem playbook that can be applied to firms of any size and in any sector As the barriers between sectors and disciplines come down, organizations everywhere will need to reshape their thinking about value propositions, competition, partnership, organizational and operating models, and performance management. The Ecosystem Economy is your personal roadmap to navigating that new world. It's ideal for managers, executives, and other business leaders seeking fresh new strategies and practical approaches for markets that bear little resemblance to the ones that came before.

Fundamental to the study of any mathematical structure is an understanding of its symmetries. In the class of Banach spaces, this leads naturally to a study of isometries-the linear transformations that preserve distances. In his foundational treatise, Banach showed that every linear isometry on the space of continuous functions on a compact metric space must transform a continuous function x into a continuous function y satisfying y(t) = h(t)x(p(t)), where p is a homeomorphism and |h| is identically one.

Isometries on Banach Spaces: Function Spaces is the first of two planned volumes that survey investigations of Banach-space isometries. This volume emphasizes the characterization of isometries and focuses on establishing the type of explicit, canonical form given above in a variety of settings. After an introductory discussion of isometries in general, four chapters are devoted to describing the isometries on classical function spaces. The final chapter explores isometries on Banach algebras.

This treatment provides a clear account of historically important results, exposes the principal methods of attack, and includes some results that are more recent and some that are lesser known. Unique in its focus, this book will prove useful for experts as well as beginners in the field and for those who simply want to acquaint themselves with this area of Banach space theory.

Mathematics in Kant's Critical Philosophy provides a much-needed reading (and re-reading) of Kant's theory of the construction of mathematical concepts through a fully contextualised analysis. In this work the author convincingly argues that it is only through an understanding of the relevant eighteenth century mathematics textbooks, and the related mathematical practice, can the material and context necessary for a successful interpretation of Kant's philosophy be provided.

The use of statistics is fundamental to many endeavors in biology and geology. For students and professionals in these fields, there is no better way to build a statistical background than to present the concepts and techniques in a context relevant to their interests. Statistics with Applications in Biology and Geology provides a practical introduction to using fundamental parametric statistical models frequently applied to data analysis in biology and geology.

Based on material developed for an introductory statistics course and classroom tested for nearly 10 years, this treatment establishes a firm basis in models, the likelihood method, and numeracy. The models addressed include one sample, two samples, one- and two-way analysis of variance, and linear regression for normal data and similar models for binomial, multinomial, and Poisson data. Building on the familiarity developed with those models, the generalized linear models are introduced, making it possible for readers to handle fairly complicated models for both continuous and discrete data. Models for directional data are treated as well. The emphasis is on parametric models, but the book also includes a chapter on the most important nonparametric tests.

This presentation incorporates the use of the SAS statistical software package, which authors use to illustrate all of the statistical tools described. However, to reinforce understanding of the basic concepts, calculations for the simplest models are also worked through by hand. SAS programs and the data used in the examples and exercises are available on the Internet.

Research in mathematics 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 mathematics. Mathematical Puzzles makes this connection explicit by isolating important mathematical methods, then using them to solve puzzles and prove a theorem. Features A collection of the world's best mathematical puzzles Each chapter features a technique for solving mathematical puzzles, examples, and finally a genuine theorem of mathematics that features that technique in its proof Puzzles that are entertaining, mystifying, paradoxical, and satisfying; they are not just exercises or contest problems.