Libros de Matemáticas, página 69 de 472

Modern apparatuses allow us to collect samples of functional data, mainly curves but also images. On the other hand, nonparametric statistics produces useful tools for standard data exploration. This book links these two fields of modern statistics by explaining how functional data can be studied through parameter-free statistical ideas. At the same time it shows how functional data can be studied through parameter-free statistical ideas, and offers an original presentation of new nonparametric statistical methods for functional data analysis.

Poincare decía que el verdadero metodo para prever el futuro de las Matemáticas consistía en estudiar su pasado y su estado actual. Así, tras un prólogo que se pregunta hacia dónde se dirigen las Matematicas, este libro presenta dos capitulos de Historia de las Matematicas que muestran pistas sobre la proyeccion futura de la evolucion del conocimiento matematico. Los dos capitulos siguientes (Geometria Algoritmica e Inteligencia Artificial) se dedican a ramas que aportan una vision actual, en relacion con otras ciencias, y abren caminos de investigacion donde las aplicaciones tecnologicas desempeñan un papel relevante. Finalmente, los capitulos 5 y 6 profundizan en cuestiones relacionadas con el aprendizaje matematico: el 5 se dedica a la formacion del profesor y su aprendizaje, y el 6 a la integracion de los procesos cognitivos y afectivos en el aprendizaje matematico.

La Incapacidad Permanente, en sus diferentes graduaciones, nace como una prestación del Sistema Español de Seguridad Social, con la vocación de suplir el déficit de ingresos que sufre un trabajador cuando, por causa de enfermedad o accidente, ve reducida o anulada su capacidad laboral.- Análisis de la jurisprudencia actual.- Legislación aplicable.- Modelos administrativos y judiciales.- Prontuario para la tramitación de la prestación.- Destinado a Abogados, áreas de recursos humanos en las empresas y en general, personas interesadas en la gestión de la prestación.

The first edition of this book has established itself as one of the leading references on generalized additive models (GAMs), and the only book on the topic to be introductory in nature with a wealth of practical examples and software implementation. It is self-contained, providing the necessary background in linear models, linear mixed models, and generalized linear models (GLMs), before presenting a balanced treatment of the theory and applications of GAMs and related models. The author bases his approach on a framework of penalized regression splines, and while firmly focused on the practical aspects of GAMs, discussions include fairly full explanations of the theory underlying the methods. Use of R software helps explain the theory and illustrates the practical application of the methodology. Each chapter contains an extensive set of exercises, with solutions in an appendix or in the books R data package gamair, to enable use as a course text or for self-study.

This highly anticipated second edition features new chapters and sections, 225 new references, and comprehensive R software. In keeping with the previous edition, this book is about the art and science of data analysis and predictive modelling, which entails choosing and using multiple tools. Instead of presenting isolated techniques, this text emphasises problem solving strategies that address the many issues arising when developing multi-variable models using real data and not standard textbook examples. Regression Modelling Strategies presents full-scale case studies of non-trivial data-sets instead of over-simplified illustrations of each method. These case studies use freely available R functions that make the multiple imputation, model building, validation and interpretation tasks described in the book relatively easy to do. Most of the methods in this text apply to all regression models, but special emphasis is given to multiple regression using generalised least squares for longitudinal data, the binary logistic model, models for ordinal responses, parametric survival regression models and the Cox semi parametric survival model. A new emphasis is given to the robust analysis of continuous dependent variables using ordinal regression.As in the first edition, this text is intended for Masters' or PhD. level graduate students who have had a general introductory probability and statistics course and who are well versed in ordinary multiple regression and intermediate algebra. The book will also serve as a reference for data analysts and statistical methodologists, as it contains an up-to-date survey and bibliography of modern statistical modelling techniques.

This book contains the ideas of functional data analysis by a number of case studies. The case studies are accessible to research workers in a wide range of disciplines. Every reader should gain not only a specific understanding of the methods of functional data analysis, but more importantly a general insight into the underlying patterns of thought. There is an associated web site with MATLABr and S?PLUSr implementations of the methods discussed.

This book is about learning from data using the Generalized Additive Models for Location, Scale and Shape (GAMLSS). GAMLSS extends the Generalized Linear Models (GLMs) and Generalized Additive Models (GAMs) to accommodate large complex datasets, which are increasingly prevalent. GAMLSS allows any parametric distribution for the response variable and modelling all the parameters (location, scale and shape) of the distribution as linear or smooth functions of explanatory variables. This book provides a broad overview of GAMLSS methodology and how it is implemented in R. It includes a comprehensive collection of real data examples, integrated code, and figures to illustrate the methods, and is supplemented by a website with code, data and additional materials.

This is the second edition of a highly succesful book which has sold nearly 3000 copies world wide since its publication in 1997. Many chapters will be rewritten and expanded due to a lot of progress in these areas since the publication of the first edition. Bernard Silverman is the author of two other books, each of which has lifetime sales of more than 4000 copies. He has a great reputation both as a researcher and an author. This is likely to be the bestselling book in the Springer Series in Statistics for a couple of years.

PERTURBATION METHODS es un libro del autor NAYFEH, ALI HASAN editado por WILEY-BLACKWELL. PERTURBATION METHODS tiene un código de ISBN 978-0-471-39917-9.

Tomo I en el que se tratan los temas concernientes a la distribución normal n-dimensional, haciendo particular enfasis en la estimación de los distintos parámetros con ella relacionados.