Functional regression is a statistical technique that extends traditional regression methods to analyze data where the predictors or responses are functions rather than scalar values. This approach is particularly useful in situations where the data can be represented as curves, surfaces, or other types of functional objects. In functional regression, the main goal is to model the relationship between a functional response variable and functional predictor variables.
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