Estimation and variable selection for partial functional linear regression (English)
- New search for: Tang, Qingguo
- Further information on Tang, Qingguo:
- https://orcid.org/0000-0003-4376-8880
- New search for: Jin, Peng
- New search for: Tang, Qingguo
- Further information on Tang, Qingguo:
- https://orcid.org/0000-0003-4376-8880
- New search for: Jin, Peng
In:
AStA Advances in Statistical Analysis
;
103
, 4
; 475-501
;
2018
-
ISSN:
- Article (Journal) / Print
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Title:Estimation and variable selection for partial functional linear regression
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Contributors:Tang, Qingguo ( author ) / Jin, Peng ( author )
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Published in:AStA Advances in Statistical Analysis ; 103, 4 ; 475-501
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Publisher:
- New search for: Springer Berlin Heidelberg
- New search for: Springer
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Place of publication:Berlin
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Publication date:2018
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ISSN:
-
ZDBID:
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DOI:
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Type of media:Article (Journal)
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Type of material:Print
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Language:English
- New search for: 31.73 / 31.73$jMathematische Statistik / 83.03$jMethoden und Techniken der Volkswirtschaft / 83.03
- Further information on Basic classification
- New search for: 519.5
- Further information on Dewey Decimal Classification
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Keywords:
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Classification:
BKL: 31.73 Mathematische Statistik / 31.73$jMathematische Statistik / 83.03$jMethoden und Techniken der Volkswirtschaft / 83.03 Methoden und Techniken der Volkswirtschaft DDC: 519.5 -
Source:
Table of contents – Volume 103, Issue 4
The tables of contents are generated automatically and are based on the data records of the individual contributions available in the index of the TIB portal. The display of the Tables of Contents may therefore be incomplete.
- 453
-
A joint quantile regression model for multiple longitudinal outcomesKulkarni, Hemant / Biswas, Jayabrata / Das, Kiranmoy et al. | 2018
- 475
-
Estimation and variable selection for partial functional linear regressionTang, Qingguo / Jin, Peng et al. | 2018
- 503
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A new approach to truncated regression for count dataMartínez-Rodríguez, Ana María / Conde-Sánchez, Antonio / Olmo-Jiménez, María José et al. | 2018
- 527
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MDCgo takes up the association/correlation challenge for grouped ordinal dataRaffinetti, Emanuela / Aimar, Fabio et al. | 2018
- 563
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Neyman-type sample allocation for domains-efficient estimation in multistage samplingKhan, M. G. M. / Wesołowski, Jacek et al. | 2018
- 593
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A unified approach to testing mean vectors with large dimensionsAhmad, M. Rauf et al. | 2018