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1988 | Dr. rer. nat., University of Heidelberg | 1988 - 1990 | Postdoc, ZI Mannheim | 1990 - 1994 | Postdoc, Institute of Economics, University of Bonn | 1994 | Habilitation (Economics), University of Bonn | 1994 - 2000 | Professor, Université Catholique de Louvain, Belgium | 2000 - 2005 | Professor (C4), University of Mainz | Since 2005 | Professor (W3), University of Bonn |
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A substantial part of my research focuses on nonparametric statistics and functional data analysis. The scientific approach incorporates the development of new methods, a study of resulting theoretical properties, and real data analysis. Important applications in economics are the study of the development of income distributions, Engel curves, and implied volatility surfaces over time or under different conditions. Biomedical applications include the analysis of human growth curves or gene expression data. Major recent contributions to this area are given in [1], [2] and [3]. A second line of my research aims at quantifying individual heterogeneity in economic panel data. In [4] it has been shown that nonparametric smoothing procedures may serve as a tool to improve efficiency of estimation of unknown factors in factor models. A third line of research considers the econometric analysis of production efficiencies based on frontier models. In a number of papers (e.g. [5], [6], [7] and [8]) we have developed a non-standard, general methodolgy for statistical inference of DEA and FDH estimators.
In the coming years I plan to study some important open problems in functional data analysis. New techniques have to be developed for the analysis of dependent data and, in particular, for time series of functions, which are important for analyzing financial data. Conventional methods for smooth functions have to be adapted in the context of non-smooth economic processes.
A major challenge is to overcome the limitations of standard Hilbert space analysis. Some important applications lead to samples of density functions which lie a nonlinear subspace of . Experiments in biomedicine frequently yield functional data possessing a common structure in terms of typical successions of peaks and valleys. The challenge then consists in identifying low-dimensional, nonlinear manifolds characterizing the data.
Crucial theoretical and methodological questions will have to be resolved. In the context of panel data I plan to consider problems of time varying and individually heterogeneous regression coefficients.
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Research Project H
Principal Investigator, since 2006
Research Area Econometrics/Statistics of the Bonn Graduate School of Economics
Principal Investigator, since 2006
DFG Cluster of Excellence “Hausdorff Center for Mathematics”
Principal Investigator
DFG project “Some current topics in conditional moment equations models: generated regressors, unknown nuisance functions and panel data”
since 2017
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[ 1] Alois Kneip, Dominik Poss, Pascal Sarda
Functional linear regression with points of impact Ann. Statist. , 44: (1): 1--30 2016 DOI: 10.1214/15-AOS1323[ 2] Christophe Crambes, Alois Kneip, Pascal Sarda
Smoothing splines estimators for functional linear regression Ann. Statist. , 37: (1): 35--72 2009 DOI: 10.1214/07-AOS563[ 3] Michal Benko, Wolfgang Härdle, Alois Kneip
Common functional principal components Ann. Statist. , 37: (1): 1--34 2009 DOI: 10.1214/07-AOS516[ 4] Alois Kneip, Robin C. Sickles, Wonho Song
A new panel data treatment for heterogeneity in time trends Econometric Theory , 28: (3): 590--628 2012 DOI: 10.1017/S026646661100034X[ 5] Alois Kneip, Léopold Simar, Paul W. Wilson
Testing hypotheses in nonparametric models of production J. Bus. Econom. Statist. , 34: (3): 435--456 2016 DOI: 10.1080/07350015.2015.1049747[ 6] Alois Kneip, Léopold Simar, Ingrid Van Keilegom
Frontier estimation in the presence of measurement error with unknown variance J. Econometrics , 184: (2): 379--393 2015 DOI: 10.1016/j.jeconom.2014.09.012[ 7] Alois Kneip, Léopold Simar, Paul W. Wilson
When bias kills the variance: central limit theorems for DEA and FDH efficiency scores Econometric Theory , 31: (2): 394--422 2015 DOI: 10.1017/S0266466614000413[ 8] A. Kneip, L. Simar, P. Wilson
A computationally efficient, consistent bootstrap for inference with non-parametric DEA estimators to appear Computational Economics 2011[ 9] Alois Kneip, Pascal Sarda
Factor models and variable selection in high-dimensional regression analysis Ann. Statist. , 39: (5): 2410--2447 2011 DOI: 10.1214/11-AOS905[ 10] Alois Kneip, James O. Ramsay
Combining registration and fitting for functional models J. Amer. Statist. Assoc. , 103: (483): 1155--1165 2008 DOI: 10.1198/016214508000000517[ 11] Alois Kneip, Klaus J. Utikal
Inference for density families using functional principal component analysis With comments and a rejoinder by the authors J. Amer. Statist. Assoc. , 96: (454): 519--542 2001 DOI: 10.1198/016214501753168235[ 13] Alois Kneip, Theo Gasser
Statistical tools to analyze data representing a sample of curves Ann. Statist. , 20: (3): 1266--1305 1992 DOI: 10.1214/aos/1176348769
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• Computational Statistics (2005 – 2010)
• Annals of Statistics (2008 - 2012)
• Bernoulli (2008 – 2010)
• Statistica Sinica, Associate Editor (since 2017)
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2003 | Elected Member, International Statistical Institute | 2019 | Fellow of the Institute of Mathematical Statistics |
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2006 | Workshop on Knowledge Extraction and Modeling, Capri, Italy | 2006 | ENSAI workshop on Nonparametric Statistics, Rennes, France | 2006 | COMPSTAT, Rome, Italy | 2006 | BIRS workshop on Statistics at the Frontiers of Science, Banff, AB, Canada | 2006 | 4èmes Journées STAPH, Grenoble, France | 2007 | Workshop on Semiparametric and Nonparametric Methods in Econometrics, Oberwolfach | 2007 | ISI 2007, Lisbon, Portugal | 2008 | WIAS workshop on Sparsity and Inverse Problems in Statistical Theory and Econometrics, Berlin | 2008 | 1st International Workshop on Functional and Operational Statistics, Toulouse, France | 2009 | BIRS workshop on Semiparametric and Nonparametric Methods in Econometrics, Banff, AB, Canada | 2009 | Congress S.Co. 2009: complex models and computational methods for estimation and prediction, Milan, Italy | 2010 | BIRS workshop on Functional Data Analysis: Future Directions, Banff, AB, Canada | 2010 | 17th Meeting of AiOs in Stochastics, Hilversum, Netherlands | 2010 | 73rd Annual Meeting of the Institute of Mathematical Statistics, Gothenburg, Sweden | 2010 | SAMSI workshop on Analysis of Object Data, Research Triangle, NC, USA | 2011 | Workshop “Efficiency measurement: new methods and application to the food sector”, Toulouse, France | 2011 | ISI world statistics conference, Dublin, Ireland | 2011 | CFE-ERCIM conference, London, England, UK | 2012 | International Society of Nonparametric Statistics conference, Haldikiki, Greece | 2012 | Workshop “Meeting the challenges of high dimension: statistical methodology, theory and applications”, Institute for Mathematical Sciences, NUS, Singapore | 2012 | Workshop on statistics of time warping and phase variations, Mathematical Biosciences Institute, Ohio State University, USA | 2013 | Workshop “Dependent functional data”, Courant Research Center, Göttingen | 2013 | Workshop “Applicable semiparametrics”, HU Berlin | 2013 | CFE-ERCIM conference, London, England, UK | 2014 | International Society of Nonparametric Statistics conference, Cadiz, Spain | 2014 | CFE-ERCIM conference, Pisa, Italy | 2015 | BIRS workshop on frontiers of functional data analysis, Banff, AB, Canada | 2015 | Workshop on recent developments in statistics for complex dependent data, Loccum | 2015 | CFE-ERCIM conference, London, England, UK | 2016 | Oberwolfach workshop “New developments in functional and highly multivariate statistical methodology”, Oberwolfach | 2016 | CRONOS workshop on functional data analysis, Oviedo, Spain |
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2011 | Chair in Statistics, University of Dortmund |
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Florence Nicole (2002): “Registration and Functional Data Analysis”,
now Associate Professor, École Nationale de l'Aviation Civile, Toulouse, France
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- Master theses: 7
- Diplom theses: 35
- PhD theses: 5
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