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Functional data analysis with R and MATLAB / J.O. Ramsay, Giles Hooker, Spencer Graves.
Tipo de material:
TextoSeries Use R! | Use R!Editor: Dordrecht ; New York, NY : Springer, c2009Descripción: xi, 207 páginas : ilustracionesTipo de contenido: - texto
- no mediado
- volumen
- 0387981845
- 9780387981840
- 519.5350285 R179f 2009
Contenidos:
Introduction to functional data analysis -- Essential comparisons of the Matlab and R languages -- How to specify basis systems for building functions -- How to build functional data objects -- Smoothing : computing curves from noisy data -- Descriptions of functional data -- Exploring variation : functional principal and canonical components analysis -- Registration : aligning features for samples of curves -- Functional linear models for scalar responses -- Linear models for functional responses -- Functional models and dynamics -- Symbol table.
| Tipo de ítem | Biblioteca actual | Colección | Signatura topográfica | Estado | Notas | Fecha de vencimiento | Código de barras | Reserva de ítems | |
|---|---|---|---|---|---|---|---|---|---|
| Libro | Biblioteca Central | Colección General | 519.5350285 R179f 2009 (Navegar estantería(Abre debajo)) | Disponible | GEN | 33409002734568 |
Total de reservas: 0
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| 519.535 S754m 2005 Making sense of multivariate data analysis / | 519.535 T112u 2024 Using multivariate statistics / | 519.535 W283a 2008 Applied statistics : from bivariate through multivariate techniques / | 519.5350285 R179f 2009 Functional data analysis with R and MATLAB / | 519.5352 B827m 1985 Multivariate analysis of variance / | 519.5352 W675a 1978 Analysis of covariance / | 519.5354 J12i 1998 Interaction effects in factorial analysis of variance / |
Incluye bibliografía.
Introduction to functional data analysis -- Essential comparisons of the Matlab and R languages -- How to specify basis systems for building functions -- How to build functional data objects -- Smoothing : computing curves from noisy data -- Descriptions of functional data -- Exploring variation : functional principal and canonical components analysis -- Registration : aligning features for samples of curves -- Functional linear models for scalar responses -- Linear models for functional responses -- Functional models and dynamics -- Symbol table.
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