Libros de estadística y probabilidad, página 31 de 120

Métodos probabilísticos y Optimización es una introducción al Cálculo de probabilidades, la Estadística paramétrica y los Métodos de optimización que subraya las aplicaciones de la probabilidad de la Ciencia de los computadores y la Teoria de la informacion, que tambien sirve como introduccion a los Procesos estocasticos o las Redes bayesianas.Su estilo es sencillo y directo, ofreciendo una reflexion sobre los aspectos fundamentales de cada una de las disciplinas que trata con el fin de servir de cimiento solido para ampliaciones posteriores del estudio.Es un texto especialmente adecuado para los estudiantes de Ingenieria electrica e Informatica.

Es de sobra conocido que Leonardo da Vinci (1452-1519) fue un polímata italiano y una de las mayores mentes creativas del Renacimiento, además del creador de la Mona Lisa y de La última cena. Lo que quizas no se sepa es que Bill Gates compro por 30 millones de dolares su cuaderno de notas original, el Codice Leicester; que era ambidiestro, con tendencias paranoides y dislexico, y que era capaz de escribir del derecho con una mano mientras, simultaneamente, escribia del reves con la otra, o que invento un coche blindado, un barco volador y las lentes de contacto. Biografico Leonardo presenta una ingeniosa guia de su vida y su obra, mediante una serie de datos y cifras impactantes convertidos en atractivas imagenes que revelan al maestro que subyace tras las obras maestras.

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Written for those who have taken a first course in statistical methods, this book takes a modern, computer-oriented approach to describe the statistical techniques used for the assessment of reliabil

This book introduces the main theoretical findings related to copulas and shows how statistical modeling of multivariate continuous distributions using copulas can be carried out in the R statistical environment with the package copula (among others). Copulas are multivariate distribution functions with standard uniform univariate margins. They are increasingly applied to modeling dependence among random variables in fields such as risk management, actuarial science, insurance, finance, engineering, hydrology, climatology, and meteorology, to name a few.In the spirit of the Use R! series, each chapter combines key theoretical definitions or results with illustrations in R. Aimed at statisticians, actuaries, risk managers, engineers and environmental scientists wanting to learn about the theory and practice of copula modeling using R without an overwhelming amount of mathematics, the book can also be used for teaching a course on copula modeling.

Principles of Copula Theory explores the state of the art on copulas and provides you with the foundation to use copulas in a variety of applications. Throughout the book, historical remarks and further readings highlight active research in the field, including new results, streamlined presentations, and new proofs of old results. After covering the essentials of copula theory, the book addresses the issue of modeling dependence among components of a random vector using copulas. It then presents copulas from the point of view of measure theory, compares methods for the approximation of copulas, and discusses the Markov product for 2-copulas. The authors also examine selected families of copulas that possess appealing features from both theoretical and applied viewpoints. The book concludes with in-depth discussions on two generalizations of copulas: quasi- and semi-copulas. Although copulas are not the solution to all stochastic problems, they are an indispensable tool for understanding several problems about stochastic dependence. This book gives you the solid and formal mathematical background to apply copulas to a range of mathematical areas, such as probability, real analysis, measure theory, and algebraic structures.

Building on the foundations of its predecessor volume, Matrix Analysis, this book treats in detail several topics in matrix theory not included in the previous volume, but with important applications and of special mathematical interest. As with the previous volume, the authors assume a background knowledge of elementary linear algebra and rudimentary analytical concepts. Many examples and exercises of varying difficulty are included.