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Functional and Operatorial Statistics

  • Conference proceedings
  • © 2008

Overview

Authors:
  1. Sophie Dabo-Niang

    1. Laboratoire GREMARS-EQUIPPE, Université Charles de Gaulle Lille 3, F-59653, France

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  2. Frédéric Ferraty

    1. Institut de Mathématiques de Toulouse Equipe LSP, Université Paul Sabatier, F-31062, France

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    You can also search for this author in PubMed   Google Scholar

Part of the book series: Contributions to Statistics (CONTRIB.STAT.)

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Table of contents (44 papers)

  1. Front Matter

    Pages i-xix
    Download chapter PDF

  2. Introduction to IWFOS'2008

    • Alain Boudou, Frédéric Ferraty, Yves Romain, Pascal Sarda, Philippe Vieu, Sylvie Viguier-Pla
    Pages 1-5

  3. Solving Multicollinearity in Functional Multinomial Logit Models for Nominal and Ordinal Responses

    • Ana Aguilera, Manuel Escabias
    Pages 7-13

  4. Estimation of Functional Regression Models for Functional Responses by Wavelet Approximation

    • Ana Aguilera, Francisco Ocaña, Mariano Valderrama
    Pages 15-21

  5. Functional Linear Regression with Functional Response: Application to Prediction of Electricity Consumption

    • Jaromír Antoch, Luboš Prchal, Maria Rosaria De Rosa, Pascal Sarda
    Pages 23-29

  6. Asymptotic Normality of Robust Nonparametric Estimator for Functional Dependent Data

    • Mohammed Attouch, Ali Laksaci, Elias Ould-Saïd
    Pages 31-34

  7. Measuring Dissimilarity Between Curves by Means of Their Granulometric Size Distributions

    • Guillermo Ayala, Martin Gaston, Teresa Leon, Fermín Mallor
    Pages 35-41

  8. Supervised Classification for Functional Data: A Theoretical Remark and Some Numerical Comparisons

    • Amparo Baíllo, Antonio Cuevas
    Pages 43-46

  9. Local Linear Regression for Functional Predictor and Scalar Response

    • Amparo Baíllo, Aurea Grané
    Pages 47-51

  10. Spatio-temporal Functional Regression on Paleoecological Data

    • Avner Bar-Hen, Liliane Bel, Rachid Cheddadi
    Pages 54-56

  11. Local Linear Functional Regression Based on Weighted Distance-based Regression

    • Eva Boj, Pedro Delicado, Josep Fortiana
    Pages 57-64

  12. Singular Value Decomposition of Large Random Matrices (for Two-Way Classification of Microarrays)

    • Marianna Bolla, Katalin Friedl, András Krámli
    Pages 65-69

  13. On Tensorial Products of Hilbertian Linear Processes

    • Denis Bosq
    Pages 71-75

  14. Recent Results on Random and Spectral Measures with Some Applications in Statistics

    • Alain Boudou, Emmanuel Cabral, Yves Romain
    Pages 77-83

  15. Parameter Cascading for High Dimensional Models

    • David Campbell, Jiguo Cao, Giles Hooker, James Ramsay
    Pages 85-88

  16. Advances in Human Protein Interactome Inference

    • Enrico Capobianco, Elisabetta Marras
    Pages 89-94

  17. Functional Principal Components Analysis with Survey Data

    • Hervé Cardot, Mohamed Chaouch, Camelia Goga, Catherine Labruère
    Pages 95-102

  18. Functional Clustering of Longitudinal Data

    • Jeng-Min Chiou, Pai-Ling Li
    Pages 103-107

  19. Robust Nonparametric Estimation for Functional Data

    • Christophe Crambes, Laurent Delsol, Ali Laksaci
    Pages 109-116

  20. Estimation of the Functional Linear Regression with Smoothing Splines

    • Christophe Crambes, Alois Kneip, Pascal Sarda
    Pages 117-120
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Keywords

About this book

An increasing number of statistical problems and methods involve infinite-dimensional aspects. This is due to the progress of technologies which allow us to store more and more information while modern instruments are able to collect data much more effectively due to their increasingly sophisticated design. This evolution directly concerns statisticians, who have to propose new methodologies while taking into account such high-dimensional data (e.g. continuous processes, functional data, etc.). The numerous applications (micro-arrays, paleo- ecological data, radar waveforms, spectrometric curves, speech recognition, continuous time series, 3-D images, etc.) in various fields (biology, econometrics, environmetrics, the food industry, medical sciences, paper industry, etc.) make researching this statistical topic very worthwhile. This book gathers important contributions on the functional and operatorial statistics fields.

Authors and Affiliations

  • Laboratoire GREMARS-EQUIPPE, Université Charles de Gaulle Lille 3, F-59653, France

    Sophie Dabo-Niang

  • Institut de Mathématiques de Toulouse Equipe LSP, Université Paul Sabatier, F-31062, France

    Frédéric Ferraty

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