Search Results - subject:"Functional Data"

Fuzzy data treated as functional data: A one-way ANOVA test approach

González-Rodríguez, Gil; Colubi, Ana; Gil, María Ángeles - In: Computational Statistics & Data Analysis 56 (2012) 4, pp. 943-955

the statistical analysis of fuzzy data by considering techniques in functional data analysis and vice versa. In this …

Persistent link: https://www.econbiz.de/10011056437

On spatial conditional mode estimation for a functional regressor

Dabo-Niang, Sophie; Kaid, Zoulikha; Laksaci, Ali - In: Statistics & Probability Letters 82 (2012) 7, pp. 1413-1421

Let (Zi=(Xi,Yi),i∈ZN) be a F×R-valued measurable strictly stationary spatial process, where F is a semi-metric space. We study a kernel estimator of the conditional mode of the univariate response variable Yi given the functional variable Xi. The main aim of this paper is to prove the almost...

Persistent link: https://www.econbiz.de/10011039785

Quantiles for finite and infinite dimensional data

Fraiman, Ricardo; Pateiro-López, Beatriz - In: Journal of Multivariate Analysis 108 (2012) C, pp. 1-14

functional data. Asymptotic properties of the empirical version of principal quantile directions are also obtained. Based on …

Persistent link: https://www.econbiz.de/10011042002

Phase and amplitude-based clustering for functional data

Slaets, Leen; Claeskens, Gerda; Hubert, Mia - In: Computational Statistics & Data Analysis 56 (2012) 7, pp. 2360-2374

Functional data that are not perfectly aligned in the sense of not showing peaks and valleys at the precise same …

Persistent link: https://www.econbiz.de/10010574461

Dynamic Functional Data Analysis with Nonparametric State Space Models.

Laurini, Márcio - IBMEC Business School - Rio de Janeiro - 2012

In this article we introduce a new methodology for modeling curves with a dynamic structure, using a non-parametric approach formulated as a state space model. The non-parametric approach is based on the use of penalized splines, represented as a dynamic mixed model. This formulation can capture...

Persistent link: https://www.econbiz.de/10010534903

Sparse estimation in functional linear regression

Lee, Eun Ryung; Park, Byeong U. - In: Journal of Multivariate Analysis 105 (2012) 1, pp. 1-17

As a useful tool in functional data analysis, the functional linear regression model has become increasingly common and …

Persistent link: https://www.econbiz.de/10010576500

Supervised classification for functional data: A weighted distance approach

Alonso, Andrés M.; Casado, David; Romo, Juan - In: Computational Statistics & Data Analysis 56 (2012) 7, pp. 2334-2346

A natural methodology for discriminating functional data is based on the distances from the observation or its …

Persistent link: https://www.econbiz.de/10010577724

On the definition of phase and amplitude variability in functional data analysis

Vantini, Simone - In: TEST: An Official Journal of the Spanish Society of … 21 (2012) 4, pp. 676-696

We introduce a modeling and mathematical framework in which the problem of registering a functional data set can be … consistently set. In detail, we show that the introduction, in a functional data analysis, of a metric/semi-metric and of a group … definition of phase and amplitude variability. Indeed, in this framework, we prove that the analysis of a registered functional …

Persistent link: https://www.econbiz.de/10010994304

Wavelet-RKHS-based functional statistical classification

Rincón, M.; Ruiz-Medina, M. - In: Advances in Data Analysis and Classification 6 (2012) 3, pp. 201-217

A functional classification methodology, based on the Reproducing Kernel Hilbert Space (RKHS) theory, is proposed for discrimination of gene expression profiles. The parameter function involved in the definition of the functional logistic regression is univocally and consistently estimated, from...

Persistent link: https://www.econbiz.de/10010995278

Spline estimators for semi-functional linear model

Zhou, Jianjun; Chen, Min - In: Statistics & Probability Letters 82 (2012) 3, pp. 505-513

In this paper, we introduce a semi-functional linear model in which a scalar response variable is explained by a linear operator of a random function and a nonparametric function of a real-valued random variable. We study the spline estimators of the functional coefficient and nonparametric...

Persistent link: https://www.econbiz.de/10010571800