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170501s2017 sz a ob 101 0 eng d |
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|a 519.5
|2 23
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| 111 |
2 |
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|a International Workshop on Functional and Operatorial Statistics
|n (4th :
|d 2017 :
|c La Coruña, Spain)
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| 245 |
1 |
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|a Functional statistics and related fields /
|c Germán Aneiros, Enea G. Bongiorno, Ricardo Cao, Philippe Vieu, editors.
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| 264 |
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1 |
|a Cham, Switzerland :
|b Springer,
|c 2017.
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| 300 |
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|a 1 online resource.
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| 336 |
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|a text
|b txt
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|a online resource
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1 |
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|a Contributions to statistics
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| 504 |
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|a Includes bibliographical references and author index.
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| 588 |
0 |
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|a Online resource; title from PDF title page (SpringerLink, viewed May 4, 2017).
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| 505 |
0 |
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|a Preface; Contents; List of Contributors; 1 An introduction to the 4th edition of the International Workshop on Functional and Operatorial Statistics ; Abstract; 1.1 Functional Data Analysis along the last decade; 1.2 On Peter Hall's impact on IWFOS conferences; 1.3 Methodological contribution for Statistics with Functional Data; 1.4 Contribution on Mathematical background for Infinite Dimensional Statistics; 1.5 Applied Functional Data Analysis contributions; 1.6 Contributions on related fields; 1.7 Concluding comments; References; 2 Robust fusion methods for Big Data; Abstract
|
| 505 |
8 |
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|a 2.1 Introduction2.2 A general setup for RFM.; 2.2.1 Breakdown point; 2.2.2 Efficiency of Fusion of M-estimators ; 2.2.3 Computational time; 2.3 Robust Fusion for covariance operator; 2.3.1 A resistant estimate of the covariance operator; 2.3.2 The impartial trimmed mean estimator; 2.3.3 Simulation results for the covariance operator; Acknowledgements; References; 3 Functional linear regression models for scalar responses on remote sensing data: an application to Oceanography; Abstract; 3.1 Introduction; 3.2 Methods; 3.3 Data; 3.3.1 In-Situ Data; 3.3.2 Satellite Data; 3.4 Results
|
| 505 |
8 |
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|a 3.5 ConclusionsAcknowledgements; References; 4 A diagonal componentwise approach for ARB(1) prediction; Abstract; 4.1 Introduction.; 4.2 Preliminaries: ARB(1) general framework and estimator of autocorrelation operator.; 4.3 Strong-consistency results: ARH(1) framework.; 4.4 Strong-consistency results: ARC(1) framework.; 4.5 Final comments and open research lines.; Acknowledgements; References; 5 A general sparse modeling approach for regression problems involving functional data; Abstract; 5.1 Difference and similarities between High Dimensional and Functional problems in Statistics
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| 505 |
8 |
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|a 5.2 A short discussion on sparse functional regression models5.3 The two-stage splitting ideas for impact points selection in functional regression; 5.3.1 Splitting the data and first rough selection; 5.3.2 Sharpening the procedure; 5.3.3 Summary of the procedure; 5.4 About the properties of the functional two-stage selection procedure; 5.5 Future work; Acknowledgements; References; 6 A time-dependent PDE regularization to model functional data defined over spatio-temporal domains ; Abstract; 6.1 Space-Time Regression with PDE Penalization; 6.2 Motivating application; References
|
| 505 |
8 |
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|a 7 An asymptotic factorization of the Small-Ball Probability: theory and estimatesAbstract; 7.1 Introduction; 7.2 Framework and Notations; 7.3 Estimates; 7.4 Conclusions; Acknowledgements; References; 8 Estimating invertible functional time series; Abstract; 8.1 Introduction; 8.2 Estimation methodology; 8.3 Algorithms; 8.4 Large-sample properties; 8.5 Empirical results; Acknowledgements; References; 9 On the Geometric Brownian Motion assumption for financial time series; Abstract; 9.1 Introduction; 9.2 Recognizing some Brownian functionals; 9.3 Analysis of financial time series; 9.3.1 Modeling
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|a Electronic resource.
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|a Mathematical statistics
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|2 local
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| 700 |
1 |
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|a Aneiros, Germán,
|e editor.
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| 700 |
1 |
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|a Bongiorno, Enea G.,
|e editor.
|
| 700 |
1 |
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|a Cao, Ricardo,
|e editor.
|
| 700 |
1 |
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|a Vieu, Philippe,
|e editor.
|0 http://id.loc.gov/authorities/names/nb2006021586
|
| 710 |
2 |
|
|a ProQuest (Firm)
|0 http://id.loc.gov/authorities/names/n2007068018
|
| 830 |
|
0 |
|a Contributions to statistics.
|0 http://id.loc.gov/authorities/names/n93034792
|
| 856 |
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|u https://ebookcentral.proquest.com/lib/tamucs/detail.action?docID=4850817
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|a Texas A&M University
|b College Station
|c Electronic Resources
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|e QA276.A1 I58 2017
|h Library of Congress classification
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| 998 |
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|a QA276.A1 I58 2017
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