Editorial: Statistics for Functional Data
Computational Statistics & Data Analysis
An overview to modelling functional data
Computational Statistics
Computational Statistics & Data Analysis
Computational Statistics & Data Analysis
Local linear regression for functional predictor and scalar response
Journal of Multivariate Analysis
Additive prediction and boosting for functional data
Computational Statistics & Data Analysis
Structural components in functional data
Computational Statistics & Data Analysis
All of Nonparametric Statistics
All of Nonparametric Statistics
Computational Statistics & Data Analysis
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The problem of nonparametrically predicting a scalar response variable from a functional predictor is considered. A sample of pairs (functional predictor and response) is observed. When predicting the response for a new functional predictor value, a semi-metric is used to compute the distances between the new and the previously observed functional predictors. Then each pair in the original sample is weighted according to a decreasing function of these distances. A Weighted (Linear) Distance-Based Regression is fitted, where the weights are as above and the distances are given by a possibly different semi-metric. This approach can be extended to nonparametric predictions from other kinds of explanatory variables (e.g., data of mixed type) in a natural way.