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Analysis of variance for functional data
Despite research interest in functional data analysis in the last three decades, few books are available on the subject. Filling this gap, Analysis of Variance for Functional Data presents up-to-date hypothesis testing methods for functional data analysis. The book covers the reconstruction of funct...
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Lenguaje: | eng |
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CRC Press
2013
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Acceso en línea: | http://cds.cern.ch/record/1604107 |
_version_ | 1780931586012741632 |
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author | Zhang, Jin-Ting |
author_facet | Zhang, Jin-Ting |
author_sort | Zhang, Jin-Ting |
collection | CERN |
description | Despite research interest in functional data analysis in the last three decades, few books are available on the subject. Filling this gap, Analysis of Variance for Functional Data presents up-to-date hypothesis testing methods for functional data analysis. The book covers the reconstruction of functional observations, functional ANOVA, functional linear models with functional responses, ill-conditioned functional linear models, diagnostics of functional observations, heteroscedastic ANOVA for functional data, and testing equality of covariance functions. Although the methodologies presented ar |
id | cern-1604107 |
institution | Organización Europea para la Investigación Nuclear |
language | eng |
publishDate | 2013 |
publisher | CRC Press |
record_format | invenio |
spelling | cern-16041072021-04-21T22:24:55Zhttp://cds.cern.ch/record/1604107engZhang, Jin-TingAnalysis of variance for functional dataMathematical Physics and MathematicsDespite research interest in functional data analysis in the last three decades, few books are available on the subject. Filling this gap, Analysis of Variance for Functional Data presents up-to-date hypothesis testing methods for functional data analysis. The book covers the reconstruction of functional observations, functional ANOVA, functional linear models with functional responses, ill-conditioned functional linear models, diagnostics of functional observations, heteroscedastic ANOVA for functional data, and testing equality of covariance functions. Although the methodologies presented arCRC Pressoai:cds.cern.ch:16041072013 |
spellingShingle | Mathematical Physics and Mathematics Zhang, Jin-Ting Analysis of variance for functional data |
title | Analysis of variance for functional data |
title_full | Analysis of variance for functional data |
title_fullStr | Analysis of variance for functional data |
title_full_unstemmed | Analysis of variance for functional data |
title_short | Analysis of variance for functional data |
title_sort | analysis of variance for functional data |
topic | Mathematical Physics and Mathematics |
url | http://cds.cern.ch/record/1604107 |
work_keys_str_mv | AT zhangjinting analysisofvarianceforfunctionaldata |