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Dimensionality reduction when data are density functions

Autor
Delicado, P.
Tipus d'activitat
Article en revista
Revista
Computational statistics and data analysis
Data de publicació
2011-01-01
Volum
55
Número
1
Pàgina inicial
401
Pàgina final
420
DOI
https://doi.org/10.1016/j.csda.2010.05.008 Obrir en finestra nova
Projecte finançador
ANALISIS DE DATOS COMPLEJOS
Repositori
http://hdl.handle.net/2117/9211 Obrir en finestra nova
URL
http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6V8V-504123R-2&_user=1517299&_coverDate=01%2F01%2F2011&_rdoc=36&_fmt=high&_orig=browse&_origin=browse&_zone=rslt_list_item&_srch=doc-info%28%23toc%235880%232011%23999449998%232346738%23FLA%23display%23Volume%29&_cdi=5880&_sort=d&_docanchor=&_ct=82&_acct=C000053450&_version=1&_urlVersion=0&_userid=1517299&md5=9af23d48133c61bf638acecd8935031c&searchtype=a Obrir en finestra nova
Resum
Functional Data Analysis deals with samples where a whole function is observed for each individual. A relevant case of FDA is when the observed functions are density functions. Among the particular characteristics of density functions, the most of the fact that they are an example of infinite dimensional compositional data (parts of some whole which only carry relative information) is made. Several dimensionality reduction methods for this particular type of data are compared: functional princip...
Citació
Delicado, P. Dimensionality reduction when data are density functions. "Computational statistics and data analysis", 01 Gener 2011, vol. 55, núm. 1, p. 401-420.
Paraules clau
Compositional data Functional data analysis Graphical output Kullback-Leibler divergence Lp distance Multidimensional scaling Population pyramids Principal components analysis
Grup de recerca
ADBD - Anàlisi de Dades Complexes per a les Decisions Empresarials

Participants