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Fruit de la collaboration des professeur Walter Hengarther de l’Université Laval, Marcel Lambert et Corina Reischer de l’Université du Québec à Trois-Rivières, Introduction à l’analyse fonctionnelle se distingue tant par l’étendue de son contenu que par l’accessibilité de sa présentation. Sans céder quoi que ce soit sur la rigueur, il est parfaitement adapté à un premier cours d’analyse fonctionnelle. Tout en étant d’abord destiné aux étudiants en mathématiques, il pourra certes être utile aux étudiants de second cycle en sciences et en génie.
Game theory—the study of how people make choices while interacting with others—is one of the most popular technical approaches in social science today. But as Michael Chwe reveals in his insightful new book, Jane Austen explored game theory’s core ideas in her six novels roughly two hundred years ago—over a century before its mathematical development during the Cold War. Jane Austen, Game Theorist shows how this beloved writer theorized choice and preferences, prized strategic thinking, and analyzed why superiors are often strategically clueless about inferiors. Exploring a diverse range of literature and folktales, this book illustrates the wide relevance of game theory and how, fundamentally, we are all strategic thinkers.
Les auteurs leur proposent donc une approche pratique et empirique qui allie l’analyse statistique à l’utilisation d’un logiciel facile d’accès : SPSS. En décrivant les diverses méthodes de l’analyse multivariée, ils présentent les interrelations entre plusieurs variables d’une base de données et en généralisent les conclusions par inférence statistique du traitement informatique des données jusqu’à l’interprétation des résultats.
As one of the classical statistical regression techniques, and often the first to be taught to new students, least squares fitting can be a very effective tool in data analysis. Given measured data, we establish a relationship between independent and dependent variables so that we can use the data predictively. The main concern of Least Squares Data Fitting with Applications is how to do this on a computer with efficient and robust computational methods for linear and nonlinear relationships. The presentation also establishes a link between the statistical setting and the computational issues. In a number of applications, the accuracy and efficiency of the least squares fit is central, and Per Christian Hansen, Víctor Pereyra, and Godela Scherer survey modern computational methods and illustrate them in fields ranging from engineering and environmental sciences to geophysics. Anyone working with problems of linear and nonlinear least squares fitting will find this book invaluable as a hands-on guide, with accessible text and carefully explained problems. Included are • an overview of computational methods together with their properties and advantages • topics from statistical regression analysis that help readers to understand and evaluate the computed solutions • many examples that illustrate the techniques and algorithms Least Squares Data Fitting with Applications can be used as a textbook for advanced undergraduate or graduate courses and professionals in the sciences and in engineering.
This book aims to illustrate with practical examples the applications of linear optimization techniques. It is written in simple and easy to understand language and has put together a useful and comprehensive set of worked examples based on real life problems.
Cet ouvrage présente un traitement mathématique rigoureux des notions fondamentales de l'algèbre linéaire et illustre son utilisation dans de nombreuses applications. Destiné aux étudiants qui sont déjà familiers avec les concepts élémentaires de l'algèbre matricielle, il répond principalement aux besoins des étudiants de premier ou de deuxième cycle en mathématiques. Les étudiants en statistique, en physique et en ingénierie y trouveront aussi leurs intérêts à travers les nombreux thèmes et applications touchant ces domaines. Chaque chapitre est agrémenté d'exercices gradués qui complètent la théorie et permettent au lecteur de vérifier sa compréhension des sujets abordés. Un recueil de solutions très détaillées des 335 exercices de ce volume est publié séparément.
The Origins of Modern Finance
March 29, 1900, is considered by many to be the day mathematical finance was born. On that day a French doctoral student, Louis Bachelier, successfully defended his thesis Théorie de la Spéculation at the Sorbonne. The jury, while noting that the topic was "far away from those usually considered by our candidates," appreciated its high degree of originality. This book provides a new translation, with commentary and background, of Bachelier's seminal work.
Bachelier's thesis is a remarkable document on two counts. In mathematical terms Bachelier's achievement was to introduce many of the concepts of what is now known as stochastic analysis. His purpose, however, was to give a theory for the valuation of financial options. He came up with a formula that is both correct on its own terms and surprisingly close to the Nobel Prize-winning solution to the option pricing problem by Fischer Black, Myron Scholes, and Robert Merton in 1973, the first decisive advance since 1900.
Aside from providing an accurate and accessible translation, this book traces the twin-track intellectual history of stochastic analysis and financial economics, starting with Bachelier in 1900 and ending in the 1980s when the theory of option pricing was substantially complete. The story is a curious one. The economic side of Bachelier's work was ignored until its rediscovery by financial economists more than fifty years later. The results were spectacular: within twenty-five years the whole theory was worked out, and a multibillion-dollar global industry of option trading had emerged.
Challenging the Myths of Mathematical Life
Mathematics is often thought of as the coldest expression of pure reason. But few subjects provoke hotter emotions--and inspire more love and hatred--than mathematics. And although math is frequently idealized as floating above the messiness of human life, its story is nothing if not human; often, it is all too human. Loving and Hating Mathematics is about the hidden human, emotional, and social forces that shape mathematics and affect the experiences of students and mathematicians. Written in a lively, accessible style, and filled with gripping stories and anecdotes, Loving and Hating Mathematics brings home the intense pleasures and pains of mathematical life.
These stories challenge many myths, including the notions that mathematics is a solitary pursuit and a "young man's game," the belief that mathematicians are emotionally different from other people, and even the idea that to be a great mathematician it helps to be a little bit crazy. Reuben Hersh and Vera John-Steiner tell stories of lives in math from their very beginnings through old age, including accounts of teaching and mentoring, friendships and rivalries, love affairs and marriages, and the experiences of women and minorities in a field that has traditionally been unfriendly to both. Included here are also stories of people for whom mathematics has been an immense solace during times of crisis, war, and even imprisonment--as well as of those rare individuals driven to insanity and even murder by an obsession with math.
This is a book for anyone who wants to understand why the most rational of human endeavors is at the same time one of the most emotional.