Problemas resueltos de matemática aplicada para ingeniería
Problemas resueltos de matemática aplicada para ingeniería

Author: GARCÍA GUIRAO, JUAN LUIS

Publisher: Ediciones Paraninfo, S.A.

Published: 2017-01-01

Total Pages: 146

ISBN-13: 8428338965

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Las (mal llamadas) clases de problemas constituyen una herramienta fundamental en cualquier disciplina científica. Tradicionalmente, estas clases cumplen el objetivo de complementar aspectos más o menos difíciles de la disciplina en cuestión. Sin embargo, deberían entenderse más como un entrenamiento que capacite al estudiante para resolver cualquier problema (en sentido amplio) que se le pueda plantear en su vida profesional. Con este espíritu se concibe esta colección de “Problemas resueltos” que Ediciones Paraninfo pone a disposición de profesores y estudiantes de una gran variedad de disciplinas académicas. En el pilar básico de esta obra está la modelización matemática de problemas de ingeniería. Se ha escrito pensando en un amplio sector de estudiantes con la ingeniería como nexo de unión. No estamos frente a un libro clásico que trate de profundizar en una materia concreta, sino que pone al alcance de los estudiantes una recopilación variada de problemas matemáticos de aplicación en el ámbito de las ingenierías, probablemente de mayor dificultad que los que se van a encontrar durante su formación universitaria básica, con el  fin de que el estudiante valore la importancia de una sólida formación matemática para un correcto desempeño profesional como ingeniero. • El capítulo 1 se centra en la modelización matemática de experimentos en el ámbito de la química. • Los capítulos 2 y 3 estudian la modelización matemática de varios problemas en el ámbito de la mecánica. • El capítulo 4 trata sobre problemas de electromagnetismo. • Se presenta un quinto capítulo con una biblioteca de herramientas en el lenguaje de programación C para resolver, con la ayuda del ordenador, la mayoría de problemas que se plantean.

Advanced Modern Engineering Mathematics
Advanced Modern Engineering Mathematics

Author: Glyn James

Publisher: Pearson Educación

Published: 1999

Total Pages: 484

ISBN-13: 9789702602095

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This second edition continues to emphasise learning by doing and the development of students' ability to use mathematics with understanding to solve engineering problems. Extensive treatment of some advanced engineering topics, particularly as tools for computer-based system modelling, analysis and design. *Follow on text from Modern Engineering Mathematics, 2E - over 20,000 copies sold *Changing student needs catered for by some easier examples and exercises plus new introductory sections on matrix algebra and vector spaces *New chapter on Numerical Solution of Ordinary Differential Equations *Engineering applications covered in specific sections in each chapter *The increasing importance of digital techniques and statistics is recognised throughout

Bayesian inference with INLA
Bayesian inference with INLA

Author: Virgilio Gomez-Rubio

Publisher: CRC Press

Published: 2020-02-20

Total Pages: 330

ISBN-13: 1351707205

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The integrated nested Laplace approximation (INLA) is a recent computational method that can fit Bayesian models in a fraction of the time required by typical Markov chain Monte Carlo (MCMC) methods. INLA focuses on marginal inference on the model parameters of latent Gaussian Markov random fields models and exploits conditional independence properties in the model for computational speed. Bayesian Inference with INLA provides a description of INLA and its associated R package for model fitting. This book describes the underlying methodology as well as how to fit a wide range of models with R. Topics covered include generalized linear mixed-effects models, multilevel models, spatial and spatio-temporal models, smoothing methods, survival analysis, imputation of missing values, and mixture models. Advanced features of the INLA package and how to extend the number of priors and latent models available in the package are discussed. All examples in the book are fully reproducible and datasets and R code are available from the book website. This book will be helpful to researchers from different areas with some background in Bayesian inference that want to apply the INLA method in their work. The examples cover topics on biostatistics, econometrics, education, environmental science, epidemiology, public health, and the social sciences.

Advanced Spatial Modeling with Stochastic Partial Differential Equations Using R and INLA
Advanced Spatial Modeling with Stochastic Partial Differential Equations Using R and INLA

Author: Elias T. Krainski

Publisher: CRC Press

Published: 2018-12-07

Total Pages: 284

ISBN-13: 0429629850

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Modeling spatial and spatio-temporal continuous processes is an important and challenging problem in spatial statistics. Advanced Spatial Modeling with Stochastic Partial Differential Equations Using R and INLA describes in detail the stochastic partial differential equations (SPDE) approach for modeling continuous spatial processes with a Matérn covariance, which has been implemented using the integrated nested Laplace approximation (INLA) in the R-INLA package. Key concepts about modeling spatial processes and the SPDE approach are explained with examples using simulated data and real applications. This book has been authored by leading experts in spatial statistics, including the main developers of the INLA and SPDE methodologies and the R-INLA package. It also includes a wide range of applications: * Spatial and spatio-temporal models for continuous outcomes * Analysis of spatial and spatio-temporal point patterns * Coregionalization spatial and spatio-temporal models * Measurement error spatial models * Modeling preferential sampling * Spatial and spatio-temporal models with physical barriers * Survival analysis with spatial effects * Dynamic space-time regression * Spatial and spatio-temporal models for extremes * Hurdle models with spatial effects * Penalized Complexity priors for spatial models All the examples in the book are fully reproducible. Further information about this book, as well as the R code and datasets used, is available from the book website at http://www.r-inla.org/spde-book. The tools described in this book will be useful to researchers in many fields such as biostatistics, spatial statistics, environmental sciences, epidemiology, ecology and others. Graduate and Ph.D. students will also find this book and associated files a valuable resource to learn INLA and the SPDE approach for spatial modeling.

RETRACTED BOOK: 151 Trading Strategies
RETRACTED BOOK: 151 Trading Strategies

Author: Zura Kakushadze

Publisher: Springer

Published: 2018-12-13

Total Pages: 480

ISBN-13: 3030027929

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The book provides detailed descriptions, including more than 550 mathematical formulas, for more than 150 trading strategies across a host of asset classes and trading styles. These include stocks, options, fixed income, futures, ETFs, indexes, commodities, foreign exchange, convertibles, structured assets, volatility, real estate, distressed assets, cash, cryptocurrencies, weather, energy, inflation, global macro, infrastructure, and tax arbitrage. Some strategies are based on machine learning algorithms such as artificial neural networks, Bayes, and k-nearest neighbors. The book also includes source code for illustrating out-of-sample backtesting, around 2,000 bibliographic references, and more than 900 glossary, acronym and math definitions. The presentation is intended to be descriptive and pedagogical and of particular interest to finance practitioners, traders, researchers, academics, and business school and finance program students.

Recent Advances in Differential Equations and Applications
Recent Advances in Differential Equations and Applications

Author: Juan Luis García Guirao

Publisher: Springer

Published: 2019-01-04

Total Pages: 250

ISBN-13: 3030003418

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This work gathers a selection of outstanding papers presented at the 25th Conference on Differential Equations and Applications / 15th Conference on Applied Mathematics, held in Cartagena, Spain, in June 2017. It supports further research into both ordinary and partial differential equations, numerical analysis, dynamical systems, control and optimization, trending topics in numerical linear algebra, and the applications of mathematics to industry. The book includes 14 peer-reviewed contributions and mainly addresses researchers interested in the applications of mathematics, especially in science and engineering. It will also greatly benefit PhD students in applied mathematics, engineering and physics.

Probability and Statistics with R
Probability and Statistics with R

Author: Maria Dolores Ugarte

Publisher: CRC Press

Published: 2008-04-11

Total Pages: 710

ISBN-13: 158488892X

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Designed for an intermediate undergraduate course, Probability and Statistics with R shows students how to solve various statistical problems using both parametric and nonparametric techniques via the open source software R. It provides numerous real-world examples, carefully explained proofs, end-of-chapter problems, and illuminating graphs

Proceedings of the International Conference of Computational Methods in Sciences and Engineering 2003 (ICCMSE 2003)
Proceedings of the International Conference of Computational Methods in Sciences and Engineering 2003 (ICCMSE 2003)

Author: T. E. Simos

Publisher: World Scientific

Published: 2003

Total Pages: 724

ISBN-13: 9789812704658

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In the past few decades, many significant insights have been gained into several areas of computational methods in sciences and engineering. New problems and methodologies have appeared in some areas of sciences and engineering. There is always a need in these fields for the advancement of information exchange. The aim of this book is to facilitate the sharing of ideas, problems and methodologies between computational scientists and engineers in several disciplines. Extended abstracts of papers on the recent advances regarding computational methods in sciences and engineering are provided. The book briefly describes new methods in numerical analysis, computational mathematics, computational and theoretical physics, computational and theoretical chemistry, computational biology, computational mechanics, computational engineering, computational medicine, high performance computing, etc.