Functional Data Analysis With R
DOWNLOAD
Download Functional Data Analysis With R PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Functional Data Analysis With R book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Functional Data Analysis With R And Matlab
DOWNLOAD
Author : James Ramsay
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-06-29
Functional Data Analysis With R And Matlab written by James Ramsay and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-06-29 with Computers categories.
Scientists often collect samples of curves and other functional observations, and develop models where parameters are also functions. This volume in the UseR! Series is aimed at a wide range of readers, and especially those who would like apply these techniques to their research problems. It complements Functional Data Analysis, Second Edition and Applied Functional Data Analysis: Methods and Case Studies by providing computer code in both the R and Matlab languages for a set of data analyses that showcase functional data analysis techniques. The authors make it easy to get up and running in new applications by adapting the code for the examples, and by being able to access the details of key functions within these pages. This book is accompanied by additional web-based support at http://www.functionaldata.org for applying existing functions and developing new ones in either language. The companion 'fda' package for R includes script files to reproduce nearly all the examples in the book including all but one of the 76 figures.
Functional Data Analysis With R
DOWNLOAD
Author : Ciprian M. Crainiceanu
language : en
Publisher: CRC Press
Release Date : 2024-03-11
Functional Data Analysis With R written by Ciprian M. Crainiceanu and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-11 with Mathematics categories.
Emerging technologies generate data sets of increased size and complexity that require new or updated statistical inferential methods and scalable, reproducible software. These data sets often involve measurements of a continuous underlying process, and benefit from a functional data perspective. Functional Data Analysis with R presents many ideas for handling functional data including dimension reduction techniques, smoothing, functional regression, structured decompositions of curves, and clustering. The idea is for the reader to be able to immediately reproduce the results in the book, implement these methods, and potentially design new methods and software that may be inspired by these approaches. Features: Functional regression models receive a modern treatment that allows extensions to many practical scenarios and development of state-of-the-art software. The connection between functional regression, penalized smoothing, and mixed effects models is used as the cornerstone for inference. Multilevel, longitudinal, and structured functional data are discussed with emphasis on emerging functional data structures. Methods for clustering functional data before and after smoothing are discussed. Multiple new functional data sets with dense and sparse sampling designs from various application areas are presented, including the NHANES linked accelerometry and mortality data, COVID-19 mortality data, CD4 counts data, and the CONTENT child growth study. Step-by-step software implementations are included, along with a supplementary website (www.FunctionalDataAnalysis.com) featuring software, data, and tutorials. More than 100 plots for visualization of functional data are presented. Functional Data Analysis with R is primarily aimed at undergraduate, master's, and PhD students, as well as data scientists and researchers working on functional data analysis. The book can be read at different levels and combines state-of-the-art software, methods, and inference. It can be used for self-learning, teaching, and research, and will particularly appeal to anyone who is interested in practical methods for hands-on, problem-forward functional data analysis. The reader should have some basic coding experience, but expertise in R is not required.
Geostatistical Functional Data Analysis
DOWNLOAD
Author : Jorge Mateu
language : en
Publisher: John Wiley & Sons
Release Date : 2021-11-16
Geostatistical Functional Data Analysis written by Jorge Mateu and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-16 with Social Science categories.
Geostatistical Functional Data Analysis Explore the intersection between geostatistics and functional data analysis with this insightful new reference Geostatistical Functional Data Analysis presents a unified approach to modelling functional data when spatial and spatio-temporal correlations are present. The Editors link together the wide research areas of geostatistics and functional data analysis to provide the reader with a new area called geostatistical functional data analysis that will bring new insights and new open questions to researchers coming from both scientific fields. This book provides a complete and up-to-date account to deal with functional data that is spatially correlated, but also includes the most innovative developments in different open avenues in this field. Containing contributions from leading experts in the field, this practical guide provides readers with the necessary tools to employ and adapt classic statistical techniques to handle spatial regression. The book also includes: A thorough introduction to the spatial kriging methodology when working with functions A detailed exposition of more classical statistical techniques adapted to the functional case and extended to handle spatial correlations Practical discussions of ANOVA, regression, and clustering methods to explore spatial correlation in a collection of curves sampled in a region In-depth explorations of the similarities and differences between spatio-temporal data analysis and functional data analysis Aimed at mathematicians, statisticians, postgraduate students, and researchers involved in the analysis of functional and spatial data, Geostatistical Functional Data Analysis will also prove to be a powerful addition to the libraries of geoscientists, environmental scientists, and economists seeking insightful new knowledge and questions at the interface of geostatistics and functional data analysis.
Data Analysis And Graphics Using R
DOWNLOAD
Author : John Maindonald
language : en
Publisher: Cambridge University Press
Release Date : 2010-05-06
Data Analysis And Graphics Using R written by John Maindonald and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-05-06 with Computers categories.
Discover what you can do with R! Introducing the R system, covering standard regression methods, then tackling more advanced topics, this book guides users through the practical, powerful tools that the R system provides. The emphasis is on hands-on analysis, graphical display, and interpretation of data. The many worked examples, from real-world research, are accompanied by commentary on what is done and why. The companion website has code and datasets, allowing readers to reproduce all analyses, along with solutions to selected exercises and updates. Assuming basic statistical knowledge and some experience with data analysis (but not R), the book is ideal for research scientists, final-year undergraduate or graduate-level students of applied statistics, and practising statisticians. It is both for learning and for reference. This third edition expands upon topics such as Bayesian inference for regression, errors in variables, generalized linear mixed models, and random forests.
Nonparametric Statistics
DOWNLOAD
Author : Michele La Rocca
language : en
Publisher: Springer Nature
Release Date : 2020-11-11
Nonparametric Statistics written by Michele La Rocca and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-11 with Mathematics categories.
Highlighting the latest advances in nonparametric and semiparametric statistics, this book gathers selected peer-reviewed contributions presented at the 4th Conference of the International Society for Nonparametric Statistics (ISNPS), held in Salerno, Italy, on June 11-15, 2018. It covers theory, methodology, applications and computational aspects, addressing topics such as nonparametric curve estimation, regression smoothing, models for time series and more generally dependent data, varying coefficient models, symmetry testing, robust estimation, and rank-based methods for factorial design. It also discusses nonparametric and permutation solutions for several different types of data, including ordinal data, spatial data, survival data and the joint modeling of both longitudinal and time-to-event data, permutation and resampling techniques, and practical applications of nonparametric statistics. The International Society for Nonparametric Statistics is a unique global organization, and its international conferences are intended to foster the exchange of ideas and the latest advances and trends among researchers from around the world and to develop and disseminate nonparametric statistics knowledge. The ISNPS 2018 conference in Salerno was organized with the support of the American Statistical Association, the Institute of Mathematical Statistics, the Bernoulli Society for Mathematical Statistics and Probability, the Journal of Nonparametric Statistics and the University of Salerno.
Air Quality Assessment Standards And Sustainable Development In Developing Countries
DOWNLOAD
Author : Weixin Yang
language : en
Publisher: MDPI
Release Date : 2020-01-07
Air Quality Assessment Standards And Sustainable Development In Developing Countries written by Weixin Yang and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-07 with Science categories.
This book brings together the latest research results of air quality assessment standards and sustainable development in developing countries. The content is full and the discussion is vivid. These articles are suitable for students and researchers at all levels seeking to understand the status of air pollution, governance standards, and governance effects in developing countries.
Information And Communication Technologies
DOWNLOAD
Author : Germania Rodriguez Morales
language : en
Publisher: Springer Nature
Release Date : 2020-11-12
Information And Communication Technologies written by Germania Rodriguez Morales and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-12 with Computers categories.
This book constitutes refereed proceedings of the 8th Conference on Information and Communication Technologies of Ecuador, TICEC 2020, held in November 2020. Due to the COVID-19 pandemic the conference was held online. The 36 full and 7 short papers were carefully reviewed and selected from 117 qualified submissions. The papers are organized according to the following topical sections: biomedical sensors and wearables systems; data science; ICT ́s applications; industry 4.0; smart cities; software development; technology and environment.
Introduction To Functional Data Analysis
DOWNLOAD
Author : Piotr Kokoszka
language : en
Publisher: CRC Press
Release Date : 2017-09-27
Introduction To Functional Data Analysis written by Piotr Kokoszka and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-27 with Mathematics categories.
Introduction to Functional Data Analysis provides a concise textbook introduction to the field. It explains how to analyze functional data, both at exploratory and inferential levels. It also provides a systematic and accessible exposition of the methodology and the required mathematical framework. The book can be used as textbook for a semester-long course on FDA for advanced undergraduate or MS statistics majors, as well as for MS and PhD students in other disciplines, including applied mathematics, environmental science, public health, medical research, geophysical sciences and economics. It can also be used for self-study and as a reference for researchers in those fields who wish to acquire solid understanding of FDA methodology and practical guidance for its implementation. Each chapter contains plentiful examples of relevant R code and theoretical and data analytic problems. The material of the book can be roughly divided into four parts of approximately equal length: 1) basic concepts and techniques of FDA, 2) functional regression models, 3) sparse and dependent functional data, and 4) introduction to the Hilbert space framework of FDA. The book assumes advanced undergraduate background in calculus, linear algebra, distributional probability theory, foundations of statistical inference, and some familiarity with R programming. Other required statistics background is provided in scalar settings before the related functional concepts are developed. Most chapters end with references to more advanced research for those who wish to gain a more in-depth understanding of a specific topic.
Spatial And Spatio Temporal Geostatistical Modeling And Kriging
DOWNLOAD
Author : José-María Montero
language : en
Publisher: John Wiley & Sons
Release Date : 2015-08-18
Spatial And Spatio Temporal Geostatistical Modeling And Kriging written by José-María Montero and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-08-18 with Mathematics categories.
Statistical Methods for Spatial and Spatio-Temporal Data Analysis provides a complete range of spatio-temporal covariance functions and discusses ways of constructing them. This book is a unified approach to modeling spatial and spatio-temporal data together with significant developments in statistical methodology with applications in R. This book includes: Methods for selecting valid covariance functions from the empirical counterparts that overcome the existing limitations of the traditional methods. The most innovative developments in the different steps of the kriging process. An up-to-date account of strategies for dealing with data evolving in space and time. An accompanying website featuring R code and examples
Data Science Classification And Artificial Intelligence For Modeling Decision Making
DOWNLOAD
Author : Javier Trejos
language : en
Publisher: Springer Nature
Release Date : 2025-04-19
Data Science Classification And Artificial Intelligence For Modeling Decision Making written by Javier Trejos and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-19 with Computers categories.
This book gathers selected and peer-reviewed contributions presented at the 18th Conference of the International Federation of Classification Societies (IFCS 2024), held in San José, Costa Rica, July 15–19, 2024. Covering a wide range of topics, it describes modern methods and real-world applications in data science, classification, and artificial intelligence related to modeling decision making. Numerous novel techniques and innovative applications are investigated, such as anomaly detection in public procurement processes, multivariate functional data clustering, air pollution prediction, benchmark generation for probabilistic planning, recommendation systems based on symbolic data analysis, and methods for clustering mixed-type data. Advanced statistical concepts are explored, including Vapnik-Chervonenkis dimensionality, Riemannian statistics, hypothesis testing for interval-valued data, and mixed models. Furthermore, machine learning techniques are applied to predict soil bacterial and fungal communities, classify electoral behavior and political competition, and assess corrosion degradation in mining pipelines. The diversity of topics discussed in this collection reflects the ongoing advancement and interdisciplinary nature of statistical and data science research, as well as its application across various fields and sectors. These studies contribute to the development of robust methodologies and efficient computational tools to address complex challenges in the era of big data. The book is intended for researchers and practitioners seeking the latest developments and applications in the field of data science and classification.