Listar por tema "functional data analysis"
Mostrando ítems 1-14 de 14
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Analysis of variance for spatially correlated functional data: Application to brain data
Elsevier (2019)Functional data showing spatial dependence structure occur in many applied fields. For example, in meteorology when curves of temperature are obtained in a monitoring network, or in neurological studies when curves of the ... -
Archetypal contour shapes
Università di Cassino e del Lazio Meridionale. Centro Editoriale di Ateneo (2019)Shapes are represented by contour functions from planar object outlines. Functional archetypal analysis is proposed to describe closed contour shapes. Each contour function is approximated by a convex combination of ... -
Classificació d'estructures cerebrals en 3D amb anàlisi de dades funcionals. Aplicació a problemes verbals amb errors d'inversió
Universitat Jaume I (2019-06-22)Una de les línies de recerca sobre les quals més s’han centrat els investigadors en els últims anys és la resolució de problemes. El cas on els estudiants no són capaços de construir una equació a partir d’un enunciat, ... -
Detecting and visualizing differences in brain structures with SPHARM and functional data analysis
Elsevier (2020-08-07)A new procedure for classifying brain structures described by SPHARM is presented. We combine a dimension reduction technique (functional principal component analysis or functional independent component analysis) with ... -
Finding archetypal patterns for binary questionnaires
Institut d'Estadística de Catalunya (Idescat) (2020-01)Archetypal analysis is an exploratory tool that explains a set of observations as mixtures of pure (extreme) patterns. If the patterns are actual observations of the sample, we refer to them as archetypoids. For the first ... -
Forecasting basketball players’ performance using sparse functional data
Wiley (2019-09)Statistics and analytic methods are becoming increasingly important in basketball. In particular, predicting players’ performance using past observations is a considerable challenge. The purpose of this study is to ... -
Functional marked point processes: a natural structure to unify spatio-temporal frameworks and to analyse dependent functional data
Springer (2020)This paper treats functional marked point processes (FMPPs), which are defined asmarked point processes where the marks are random elements in some (Polish) func-tion space. Such marks may represent, for example, spatial ... -
Generalized Linear Models for Geometrical Current predictors. An application to predict garment fit
SAGE Publications (2019)The aim of this paper is to model an ordinal response variable in terms of vector-valued functional data included on a vector-valued RKHS. In particular, we focus on the vector-valued RKHS obtained when a geometrical ... -
Heteroskedastic geographically weighted regression model for functional data
Elsevier (2020)A large number of approaches for modelling spatially dependent functional variables often assume that the functional regression coefficients are constant over the region of interest. However, in many occasions it is far ... -
Ordinal classification for interval-valued data and interval-valued functional data
Elsevier (2023-10-29)The aim of ordinal classification is to predict the ordered labels of the output from a set of observed inputs. Interval-valued data refers to data in the form of intervals. For the first time, interval-valued data and ... -
Robust archetypoids for anomaly detection in big functional data
Springer (2020-08-03)Archetypoid analysis (ADA) has proven to be a successful unsupervised statistical technique to identify extreme observations in the periphery of the data cloud, both in classical multivariate data and functional data. ... -
Statistics for spatial functional data: some recent contributions
John Wiley & Sons, Ltd. (2010)Functional data analysis (FDA) is a relatively new branch in statistics. Experiments where a complete function is observed for each individual give rise to functional data. In this work we focus on the case of functional ... -
Supervised classification of geometrical objects by integrating currents and functional data analysis
Springer Verlag (2019)This paper focuses on the application of supervised classification techniques to a set of geometrical objects (bodies) characterized by currents, in particular, discriminant analysis and some nonparametric methods. A current ... -
Técnicas de clasificación para datos funcionales. Aplicación a series temporales de número de positivos en Covid 19 por departamento de salud de la Comunitat Valenciana
Universitat Jaume I (2022-07-18)En este trabajo se analizan los m´etodos b´asicos de clasificaci´on supervisada y no supervisada para datos funcionales. Hemos partido de una muestra de series temporales, en concreto la “Serie de casos con PDIA positiva ...