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In an age of big data, data journalism and with a wealth of quantitative information around us, it is not enough for students to be taught only 100 year old statistical methods using 'out of the box' software. They need to have 21st-century analytical skills too. This is an excellent and student-friendly text from two of the world leaders in the teaching and development of spatial analysis. It shows clearly why the open source software R is not just an alternative to commercial GIS, it may actually be the better choice for mapping, analysis and for replicable research. Providing practical tips as well as fully working code, this is a practical 'how to' guide ideal for undergraduates as well as those using R for the first time. It will be required reading on my own courses." - Richard Harris, Professor of Quantitative Social Science, University of Bristol R is a powerful open source computing tool that supports geographical analysis and mapping for the many geography and `non-geography' students and researchers interested in spatial analysis and mapping. This book provides an introduction to the use of R for spatial statistical analysis, geocomputation and the analysis of geographical information for researchers collecting and using data with location attached, largely through increased GPS functionality. Brunsdon and Comber take readers from `zero to hero' in spatial analysis and mapping through functions they have developed and compiled into R packages. This enables practical R applications in GIS, spatial analyses, spatial statistics, mapping, and web-scraping. Each chapter includes: Example data and commands for exploring itScripts and coding to exemplify specific functionalityAdvice for developing greater understanding - through functions such as locator(), View(), and alternative coding to achieve the same ends Self-contained exercises for students to work throughEmbedded code within the descriptive text. This is a definitive 'how to' that takes students - of any discipline - from coding to actual applications and uses of R.

Covers the substantial advances that have taken place in the field during the last 15 years, including vine copula modeling of high-dimensional data. Vine copula models are constructed from a sequence of bivariate copulas. The book develops generalizations of vine copula models, including common and structured factor models that extend from the Gaussian assumption to copulas. It also discusses other multivariate constructions and parametric copula families that have different tail properties and presents extensive material on dependence and tail properties to assist in copula model selection.The author shows how numerical methods and algorithms for inference and simulation are important in high-dimensional copula applications. He presents the algorithms as pseudocode, illustrating their implementation for high-dimensional copula models. He also incorporates results to determine dependence and tail properties of multivariate distributions for future constructions of copula models.

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Longitudinal studies often incur several problems that challenge standard statistical methods for data analysis. These problems include non-ignorable missing data in longitudinal measurements of one or more response variables, informative observation times of longitudinal data, and survival analysis with intermittently measured time-dependent covariates that are subject to measurement error and/or substantial biological variation. Joint modeling of longitudinal and time-to-event data has emerged as a novel approach to handle these issues. Joint Modeling of Longitudinal and Time-to-Event Data provides a systematic introduction and review of state-of-the-art statistical methodology in this active research field. The methods are illustrated by real data examples from a wide range of clinical research topics. A collection of data sets and software for practical implementation of the joint modeling methodologies are available through the book website. This book serves as a reference book for scientific investigators who need to analyze longitudinal and/or survival data, as well as researchers developing methodology in this field. It may also be used as a textbook for a graduate level course in biostatistics or statistics.

Springer-Verlag New York Inc., United States, 2010. Paperback. Book Condition: New. Language: English . Brand New Book ***** Print on Demand *****.This volume, which is completely dedicated to continuous bivariate dist- butions, describes in detail their forms, properties, dependence structures, computation, and applications. It is a comprehensive and thorough revision ofanearliereditionof ContinuousBivariateDistributions,Emphasizing- plications by T.P. Hutchinson and C.D. Lai, published in 1990 by Rumsby Scienti?c Publishing, Adelaide, Australia. It has been nearly two decades since the publication of that book, and much has changed in this area of research during this period. Generali- tions have been considered for many known standard bivariate distributions. Skewed versions of di?erent bivariate distributions have been proposed and appliedtomodeldatawithskewnessdepartures.Byspecifyingthetwocon- tional distributions, rather than the simple speci?cation of one marginal and one conditional distribution, several general families of conditionally spe- ?ed bivariate distributions have been derived and studied at great length. Finally, bivariate distributions generated by a variety of copulas and their ?exibility (in terms of accommodating association/correlation) and str- tural properties have received considerable attention. All these developments andadvancesnecessitatedthepresentvolumeandhavethusresultedinas- stantially di?erent version than the last edition, both in terms of coverage and topics of discussion. Softcover reprint of hardcover 2nd ed. 2009. Bookseller Inventory # AAV9781441918758

"Miguel Pérez-Moneo y Joan Vintró Castells con profesores de Derehco Constitucional de la Universitat de Barcelona. Coordinan este libro en el que participan otros 16 profesores de Derehco Constitucional de distintas Universidades: Carlos III Y Complutense de Madrid, de León, de Oviedo y Universidad de Educación a distancia". Este libro colectivo presenta una reflexión sobre la participación política a partir de la consideración de diversos mecanismos participativos que tienen en cuenta al ciudadano tanto en su condición de individuo como de representado político......

El informe clínico ha de servir para valorar, a través de la historia clínica del paciente, las pruebas realizadas de evaluación y diagnóstico, y en su caso el tratamiento o intervención, el estado en el que se encuentra el sujeto y las indicaciones que debera seguir en el futuro.El hecho de elaborar con correccion tecnica y linguistica los informes ayuda a todos: padres, familiares, medicos, logopedas y pacientes.En esta Guia Practica se ofrece una ayuda a los profesionales de la logopedia en su practica diaria en la redaccion y elaboracion de informes. Cada vez son mas las personas que por diferentes motivos cambian de centro sanitario o educativo y la unica informacion que tiene el nuevo facultativo o educador sobre estos pacientes es el informe clinico realizado previamente. Es por ello, que sea tan importante que este redactado con coherencia y claridad.Entre las principales caracteristicas de este libro destacan: Marca unas determinadas pautas de eficiencia para la elaboracion de los informes clinicos. Aporta conocimientos, valores, actitudes y buenas practicas partiendo de la experiencia clinica y educativa de los profesionales de la logopedia. Incluye informes realizados por logopedas de España e Hispanoamerica para explicar de forma practica como se realiza esta labor de redaccion tan necesaria.Hay que tener muy presente la importancia que la correcta redaccion de un informe tiene en la implicacion y recuperacion del paciente, por lo que esta obra sera de gran utilidad tanto a profesionales como estudiantes de logopedia que comienzan su andadura en el contexto laboral.

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.