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: https://doi.org/10.1111/rssb.12155



Papers and Publications



Recent Publications


Carvalho, V. M., Nirei, M., Saito, Y. U. and Tahbaz-Salehi, A. Supply Chain Disruptions: Evidence from the Great East Japan Earthquake Quarterly Journal of Economics [2021]

Galeotti, A., Golub, B. and Goyal, S. Targeting Interventions in Networks Econometrica [2020]

Todd, P. E. and Zhang, W. A Dynamic Model of Personality, Schooling, and Occupational Choice Quantitative Economics [2020]

Dziubinski, M., Goyal, S. and Minarsch, D. E. N. The Strategy of Conquest Journal of Economic Theory [2021]