skip to content

Faculty of Economics

Journal Cover

Vogt, M. and Linton, O.

Classification of non-parametric regression functions in longitudinal data models

Journal of the Royal Statistical Society. Series B: Statistical Methodology

Vol. 79(1) pp. 5-27 (2017)

Abstract: We investigate a longitudinal data model with non-parametric regression functions that may vary across the observed individuals. In a variety of applications, it is natural to impose a group structure on the regression curves. Specifically, we may suppose that the observed individuals can be grouped into a number of classes whose members all share the same regression function. We develop a statistical procedure to estimate the unknown group structure from the data. Moreover, we derive the asymptotic properties of the procedure and investigate its finite sample performance by means of a simulation study and a real data example.

Keywords: Classification of regression curves, Kernel estimation, Longitudinal or panel data, Non-parametric regression

Author links: Oliver Linton  

Publisher's Link: http://onlinelibrary.wiley.com/doi/10.1111/rssb.12155/full



Papers and Publications



Recent Publications


Fruehwirth, J., Iyer, S. and Zhang, A. Religion and Depression in Adolescence Journal of Political Economy [2019]

Elliott, M. and Golub, B. A Network Approach to Public Goods Journal of Political Economy [2019]

Dziubinski, M., Goyal, S. and Minarsch, D. E. N. The Strategy of Conquest Journal of Economic Theory, forthcoming [2020]

Bergin, P. R. and Corsetti, G. Beyond Competitive Devaluations: The Monetary Dimensions of Comparative Advantage American Economic Journal: Macroeconomics [2020]