Figure 1: Ozone Example. Daily trajectories of ground-level concentrations of (a) oxides of nitrogen and (b) ozone in the city of Sacramento in the Summer of 2005. The data is shown in Figure 1. The goal is to predict ozone concentration from oxides of nitrogen. Both types of curves follow regular patterns, but some atypical curves can be discerned in the sample. We will show in Section 4 that to a large extend it is indeed pos- sible to predict ozone levels from oxides-of-nitrogen levels, but that the outlying curves distort the classical regression estimators and that the proposed robust method gives more reliable results. The paper is organized as follows. Section 2 presents a brief overview of functional linear regression and introduces the new method. Section 3 reports the results of a compar- ative simulation study, and Section 4 presents a detailed analysis of the above mentioned ozone dataset. Technical derivations and proofs are left to the Appendix. Matlab R ○ pro- grams implementing these procedures are available on the author’s webpage. 2