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Aggiungi al carrelloCondizione: New.
Condizione: New. 1st edition NO-PA16APR2015-KAP.
Condizione: As New. Unread book in perfect condition.
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 101,44
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Editore: Chapman and Hall/CRC 2024-03-11, 2024
ISBN 10: 1032244712 ISBN 13: 9781032244716
Lingua: Inglese
Da: Chiron Media, Wallingford, Regno Unito
EUR 98,97
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Aggiungi al carrelloHardcover. Condizione: New.
Da: Majestic Books, Hounslow, Regno Unito
EUR 108,79
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Condizione: New.
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Aggiungi al carrelloHardcover. Condizione: Brand New. 336 pages. 9.19x6.13x1.02 inches. In Stock.
Editore: Taylor and Francis Ltd, GB, 2024
ISBN 10: 1032244712 ISBN 13: 9781032244716
Lingua: Inglese
Da: Rarewaves.com USA, London, LONDO, Regno Unito
Prima edizione
EUR 151,82
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Aggiungi al carrelloHardback. Condizione: New. 1st. 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 softwareThe connection between functional regression, penalized smoothing, and mixed effects models is used as the cornerstone for inferenceMultilevel, longitudinal, and structured functional data are discussed with emphasis on emerging functional data structuresMethods for clustering functional data before and after smoothing are discussedMultiple 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 studyStep-by-step software implementations are included, along with a supplementary website featuring software, data, and tutorialsMore than 100 plots for visualization of functional data are presentedFunctional 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.
EUR 110,33
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Aggiungi al carrelloCondizione: New. Ciprian M. Crainiceanu is Professor of Biostatistics at Johns Hopkins University working on wearable and implantable technology (WIT), signal processing, and clinical neuroimaging. He has extensive experience in mixed effects modeling, semiparamet.
EUR 156,81
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Aggiungi al carrelloHardcover. Condizione: Brand New. 336 pages. 9.19x6.13x1.02 inches. In Stock.
Editore: Taylor and Francis Ltd, GB, 2024
ISBN 10: 1032244712 ISBN 13: 9781032244716
Lingua: Inglese
Da: Rarewaves.com UK, London, Regno Unito
Prima edizione
EUR 144,12
Quantità: 1 disponibili
Aggiungi al carrelloHardback. Condizione: New. 1st. 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 softwareThe connection between functional regression, penalized smoothing, and mixed effects models is used as the cornerstone for inferenceMultilevel, longitudinal, and structured functional data are discussed with emphasis on emerging functional data structuresMethods for clustering functional data before and after smoothing are discussedMultiple 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 studyStep-by-step software implementations are included, along with a supplementary website featuring software, data, and tutorialsMore than 100 plots for visualization of functional data are presentedFunctional 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.
Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 112,65
Quantità: 4 disponibili
Aggiungi al carrelloCondizione: New. PRINT ON DEMAND.