Libros de estadística y probabilidad, página 10 de 110

Este compendio de tablas estadísticas permite disponer de los valores criterio necesarios para estudiar la significación de la gran mayoría de pruebas estadísticas que se utilizan en la actualidad. Esta tercera edicion incluye nuevas tablas que permiten analizar, por ejemplo, la potencia de una prueba o la correccion de Sidak.Aquest material didactic de la Universitat de les Illes Balears, compendi de taules estadistiques, permet disposar dels valors criteri necessaris per estudiar la significacio de la majoria de proves estadistiques que s'utilitzen en l'actualitat. Aquesta tercera edicio inclou noves taules que permeten analitzar, per exemple, la potencia d'una prova o la correccio de Sidak.This compendium of statistical tables provides the values needed to study the significance of the majority of statistical tests used today. This third edition includes new tables to analyze, for example, the power of a test or the Sidak correction.

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.

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.

Winner of the 2016 De Groot Prize from the International Society for Bayesian Analysis Now in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. Bayesian Data Analysis, Third Edition continues to take an applied approach to analysis using up-to-date Bayesian methods. The authors-all leaders in the statistics community-introduce basic concepts from a data-analytic perspective before presenting advanced methods. Throughout the text, numerous worked examples drawn from real applications and research emphasize the use of Bayesian inference in practice. New to the Third Edition * Four new chapters on nonparametric modeling * Coverage of weakly informative priors and boundary-avoiding priors * Updated discussion of cross-validation and predictive information criteria * Improved convergence monitoring and effective sample size calculations for iterative simulation * Presentations of Hamiltonian Monte Carlo, variational Bayes, and expectation propagation * New and revised software code The book can be used in three different ways. For undergraduate students, it introduces Bayesian inference starting from first principles. For graduate students, the text presents effective current approaches to Bayesian modeling and computation in statistics and related fields. For researchers, it provides an assortment of Bayesian methods in applied statistics. Additional materials, including data sets used in the examples, solutions to selected exercises, and software instructions, are available on the book's web page.

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.

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 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.

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.

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.

Spatial and Spatio-Temporal Bayesian Models with R-INLA provides a much needed, practically oriented & innovative presentation of the combination of Bayesian methodology and spatial statistics. The authors combine an introduction to Bayesian theory and methodology with a focus on the spatial and spatio--temporal models used within the Bayesian framework and a series of practical examples which allow the reader to link the statistical theory presented to real data problems. The numerous examples from the fields of epidemiology, biostatistics and social science all are coded in the R package R-INLA, which has proven to be a valid alternative to the commonly used Markov Chain Monte Carlo simulations

"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......

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.

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

La obra expone los lineamientos básicos de estadística descriptiva y probabilidades para ingenieros. Así, la estadística es un método científico requerido en todo trabajo de investigación, ya que permite recolectar, describir y analizar datos, con el proposito de enmendar errores e innovar las relaciones humanas.El libro proporciona las herramientas basicas e indispensables de la estadistica, y asi manejar con eficiencia la informacion requerida para una adecuada toma de decisiones. Por ello, se desarrollan temas, como estadistica descriptiva, distribuciones bidimensionales y probabilidades.Este libro esta dirigido a los ingenieros, quienes requieren del metodo cientifico de la estadistica descriptiva y probabilidades para los fines practicos de su especialidad.

Este libro desarrolla los conceptos necesarios para la aplicación del método estadístico a diversas disciplinas. La estadística se encarga de diseñar, recolectar, describir, analizar e interpretar la informacion y, por ello, constituye la metodologia cientifica principal que permite transformar datos en informacion. La obra tiene como objetivo ser una herramienta que ayude a los usuarios a procesar y analizar la informacion de forma facil y sencilla. Por ello, desarrolla temas como estadistica descriptiva, graficos descriptivos, distribuciones bidimensionales, coeficiente de correlacion lineal, analisis combinatorio, distribuciones de probabilidad e inferencia estadistica, entre otros. El presente libro esta dirigido a ingenieros, cientificos y estudiantes de las carreras de Administracion, Direccion de Empresas, Economia, Sociologia, Relaciones Laborales, entre otras.Este libro desarrolla los conceptos necesarios para la aplicación del método estadístico a diversas disciplinas. La estadística se encarga de diseñar, recolectar, describir, analizar e interpretar la informacion y, por ello, constituye la metodologia cientifica principal que permite transformar datos en informacion. La obra tiene como objetivo ser una herramienta que ayude a los usuarios a procesar y analizar la informacion de forma f...