Journal Article10.1016/J.ECOSTA.2017.07.001
Binary functional linear models under choice-based sampling
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TL;DR: In this paper, a functional binary choice model is explored in a case-control or choice-based sample design context, where the response is binary, the explanatory variable is functional, and the sample is stratified with respect to the values of the response variable.
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About: This article is published in Econometrics and Statistics. The article was published on 01 Jul 2017. The article focuses on the topics: Choice set & Sampling (statistics).
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References
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J. O. Ramsay
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TL;DR: The article considers general issues such as characteristics of functional data, uses of derivatives in functional modelling, estimation of phase variation by the alignment or registration of curve features, the nature of error, and so forth.
Functional Data Analysis
TL;DR: Functional data analysis (FDA) models data using functions or functional parameters.
Functional PLS logit regression model
TL;DR: A functional partial least squares logit regression model is proposed, that has as covariates a set of partial least square components of the design matrix of the multiple logit model associated to the functional one.
Functional Regression: A New Model for Predicting Market Penetration of New Products
TL;DR: The insights to be gained and predictive performance of functional data analysis (FDA), a new class of nonparametric techniques that has shown impressive results within the statistics community, on the market penetration of 760 categories drawn from 21 products and 70 countries are demonstrated.