Solving Multicollinearity in Functional Multinomial Logit Models for Nominal and Ordinal Responses
Difierent functional logit models to estimate a multicategory response variable from a functional predictor will be formulated in terms of difierent types of logit transformations as base-line category logits for nominal responses or cumulative, adjacent-categories or continuation-ratio logits for ordinal responses. Estimation procedures of functional logistic regression based on functional PCA of sample curves will be generalized to the case of a multicategory response. The true functional form of sample curves will be reconstructed in terms of basis expansions whose coeficients will be estimated from irregularly distributed discrete time observations.
KeywordsOrdinal Response Logit Transformation Functional Principal Component Analysis Functional Principal Component Binary Logit Model
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