Libros de estadística y probabilidad, página 13 de 110

Designed for courses on Evolutionary Multi-objective Optimization and Evolutionary Algorithms.This textbook is the second edition of Evolutionary Algorithms for Solving Multi-Objective Problems, significantly augmented with contemporary knowledge and adapted for the classroom. All the various features of multi-objective evolutionary algorithms (MOEAs) are presented in an innovative and student-friendly fashion, incorporating state-of-the-art research results. The diversity of serial and parallel MOEA structures are given, evaluated and compared. The book provides detailed insight into the application of MOEA techniques to an array of practical problems. The assortment of test suites are discussed along with the variety of appropriate metrics and relevant statistical performance techniques.Distinctive features of the new edition include:- Designed for graduate courses on Evolutionary Multi-Objective Optimization, with exercises and links to a complete set of teaching material including tutorials.- Updated and expanded MOEA exercises, discussion questions and research ideas at the end of each chapter.- New chapter devoted to coevolutionary and memetic MOEAs with added material on solving constrained multi-objective problems.- Additional material on the most recent MOEA test functions and performance measures, as well as on the latest developments on the theoretical foundations of MOEAs.- An exhaustive index and bibliography.This self-contained reference is invaluable to students, researchers and in particular to computer scientists, operational research scientists and engineers working in evolutionary computation, genetic algorithms and artificial intelligence.

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.

Se analizan todas las situaciones que involucran la comparación de dos grupos, desde las perspectivas paramétrica, no paramétrica, robusta, exacta y de comparación de modelos, en los escenarios de las pruebas de conformidad, de comparacion en grupos independientes y en medidas repetidas. Se proporcionan las sintaxis de SPSS y de R para obtener las soluciones a las cuestiones practicas, y se analizan conceptos tan importantes como el intervalo de confianza, el tamaño del efecto o la potencia de la prueba. Por todo ello, resulta de especial interes para el investigador aplicado asi como libro de texto para cursos de Estadistica.S''analitzen totes les situacions que involucren la comparacio de dos grups, des de les perspectives parametrica, no parametrica, robusta, exacta i de comparacio de models, en els escenaris de les proves de conformitat, de comparacio en grups independents i en mesures repetides. Resulta d''interes per a l''investigador i com a llibre de text per a cursos d''Estadistica.

Capítulo 1: muestreo y estadística descriptiva. Capítulo 2-. Aspectos básicos de ibm spss y estadística descriptiva. Capítulo 3: Inferencia estadística. Capítulo 4: Inferencia estadística con IBM SPS

Este libro contiene una colección de problemas propuestos de Probabilidad y Estadística, clasificados según su dificultad, resueltos de varias formas posibles y con gran nivel de detalle. Se incluye una breve sinopsis de los contenidos teoricos requeridos al principio de cada capitulo.

Este manual supone una amplia revisión de las notas de clase elaboradas por el autor para los alumnos de Estadística I, cuya docencia corresponde al Departamento de Estadística y Econometría de la Universidad de Malaga. Persigue dos objetivos. El primero, introducirles en los fundamentos teoricos y practicos de la Estadistica Descriptiva y de la Teoria de la Probabilidad, enfatizando su utilidad para una correcta formacion en el ambito socioeconomico. El segundo, proporcionarles suficiente material como para superar las pruebas de evaluacion a las que se enfrenten. Todas las lecciones incluidas cuentan con numerosos ejemplos y ejercicios resueltos y propuestos. La obra se divide en dos bloques. El primero corresponde al campo de la Estadistica Descriptiva. La leccion 1 asienta las definiciones que resultan basicas para el resto del curso e introduce al lector en los metodos y tecnicas propios del analisis univariante. El estudio de las caracteristicas de una distribucion se realiza a partir de la obtencion e interpretacion de medidas de tendencia central, de dispersion, de forma y de desigualdad. Por su parte, la leccion 2 tiene como objetivo general proporcionar las herramientas basicas para el estudio de la relacion entre dos variables. El discurso se centra en el analisis grafico, la covarianza y el coeficiente de correlacion. La leccion 3, ultima de este primer bloque, proporciona las claves necesarias para la correcta elaboracion e interpretacion de numeros indices, tanto simples como complejos, y de tasas de variacion. El segundo bloque sirve de introduccion para la materia que se aborda tanto en cursos de Inferencia Estadistica como de Econometria. En la leccion 4, se revisan los conceptos basicos de la Teoria de la Probabilidad, se aborda su definicion axiomatica y los distintos metodos de asignacion de probabilidades. Tambien se dedican lineas a la definicion de la probabilidad condicionada y a la caracterizacion de la independencia de sucesos. La leccion 5 se consagra al concepto de variable aleatoria y a todo lo que le rodea. Se introducen las nociones de funcion de densidad y de distribucion, momentos, esperanza matematica y varianza. Cuando el analisis se amplia a dos variables aleatorias, resultan fundamentales los conceptos de funcion de densidad conjunta, marginal y condicionada. Al termino de esta leccion se aborda lo relativo a la covarianza, el coeficiente de correlacion, la independencia de variables aleatorias y la linea de regresion. En las lecciones 6 y 7 se revisan las principales caracteristicas de los modelos de probabilidad aplicables a variables aleatorias discretas y continuas, respectivamente. En concreto, en la leccion 6 se describen los modelos Binomial, Poisson, Hipergeometrico y Multinomial, mientras que en la leccion 7, las distribuciones uniforme, gamma, exponencial, ji-dos, Normal, t de Student, F de Snedecor y normal bivariante.

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.

"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......

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.

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.

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.

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.

Aquest manual recull uns apunts preparats per fer l'assignatura "Anàlisi de dades i introducció a la probabilitat", del Grau de Matemàtiques de la Universitat de Barcelona..Es tracta d'una assignatur

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.

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.

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.

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

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