Abstract
When predicting scalar responses in the situation where the explanatory variables are functions, it is sometimes the case that some functional variables are related to responses linearly while other variables have more complicated relationships with the responses. In this paper, we propose a new semi-parametric model to take advantage of both parametric and nonparametric functional modelling. Asymptotic properties of the proposed estimators are established and finite sample behaviour is investigated through a small simulation experiment. © American Statistical Association and Taylor & Francis 2011.
| Original language | English |
|---|---|
| Pages (from-to) | 115-128 |
| Journal | Journal of Nonparametric Statistics |
| Volume | 23 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - Mar 2011 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Research Keywords
- Functional data
- Kernel regression
- Partial linear model
- Rates of convergence
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