Nonparametric Functional Data Analysis: Theory And Practice

By Z. Q. J. Lu. 2007

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Citations in the corpus

Fast Distribution To Real Regression (2013, background): “This is a great improvement over the linear scaling with N that the Kernel-Kernel (KK) estimator has and allows one to explore DRR in new domains with large collections of distributions, such as astronomy and ﬁnance.”
Distribution-Free Distribution Regression (2013, methodology): “Our results are distribution free, similar to the functional regression case Ferraty and Vieu [2006], in the sense that we do not make any strong distributional assumptions.”
Rainbow Plots, Bagplots, and Boxplots for Functional Data (2010, background): “Ramsay & Silverman (2005) and Ferraty & Vieu (2006) provide detailed surveys of the many parametric and nonparametric techniques for analyzing functional data.”
Modeling and forecasting electricity spot prices: A functional data perspective (2013, methodology): “For example, there is a vast literature on modeling and forecasting electricity demand; see, for example, Ferraty and Vieu (2006) and Antoch et al. (2010).”
Distances and inference for covariance operators (2014, methodology): “In recent years, many statistical techniques have been proposed to deal with functional data (see, e.g., Ramsay & Silverman, 2005; Ferraty & Vieu, 2006; Horváth & Kokoszka, 2012).”
The functional linear array model (2015, background): “Functional data analysis (Ramsay and Silverman, 2005; Ferraty and Vieu, 2006) aims at analyzing data where the observation units are functions.”
Mean estimation with data missing at random for functional covariables (2013, background): “Statistics, 2013 Vol. 47, No. 4, 688–706, http://dx.doi.org/10.1080/02331888.2011.650172 Mean estimation with data missing at random for functional covariables Frédéric Ferratya, Mariela Suedb* and Philippe Vieua aInstitut de Mathématiques, Université Paul Sabatier, Toulouse, France; bFacultad de Ci”
Cross-validated estimations in the single-functional index model (2008, methodology): “In order to highlight the specificity of such a single-functional index model, the obtained predictions are compared with those coming from a ‘pure’ nonparametric functional data analysis (NPFDA) method (see [8] for details and references therein).”
A Geometric Approach to Maximum Likelihood Estimation of the Functional Principal Components From Sparse Longitudinal Data (2007, background): “Ramsay and Silverman (2005) and Ferraty and Vieu (2006) gave an extensive survey of the applications of functional principal components analysis (FPCA).”
Asymptotics of prediction in functional linear regression with functional outputs (2009, methodology): “Important nonparametric issues are treated in the monograph by Ferraty and Vieu [13].”
Penalized Functional Regression (2011, neutral): “…are functions (James 2002; Cardot, Ferraty, and Sarda 2003; Cardot and Sarda 2005; James and Silverman 2005; Müller 2005; Ramsay and Silverman 2005; Ferraty and Vieu 2006; Reiss and Ogden 2007; Jeff Goldsmith is Ph.D. Candidate (E-mail: jgoldsmi@jhsph.edu), Jennifer Bobb is Ph.D. Candidate…”
NONPARAMETRIC REGRESSION ON FUNCTIONAL DATA: INFERENCE AND PRACTICAL ASPECTS (2007, methodology): “…literature addresses either the statement of upper bounds of the rates of convergence without specification of the exact constants (see Chapter 6 in Ferraty & Vieu, 2006), or abstract expressions of these constants, which are unusable in practice (e.g. in the recent work by Masry (2005), which was…”
A survey of functional principal component analysis (2014, background): “( 2007 ) , Ferraty & Vieu ( 2006 ) , Mas ( 2002 ) , Mas ( 2008 ) , Bosq ( 2000 ) , among many others .”
On the Local Linear Modelization of the Conditional Distribution for Functional Data (2014, background): “Notice that, questions on the statistical modelization of the functional data have known a growing interest among theoretical and applied statistics (cf. Bosq, 2000; Ramsay and Silverman, 2002a, 2002b for parametric models and Ferraty and Vieu (2006) for the nonparametric case).”
Outlier detection in functional data by depth measures, with application to identify abnormal NOx levels (2008, background): “See Ferraty and Vieu (2006) for more details on this approach.”
A moving window approach for nonparametric estimation of the conditional tail index (2008, background): “It describes how the design points concentrate in the neighborhood of t when hn,t goes to zero, similarly to the small ball probability does, see for instance the monograph on functional data analysis [18].”