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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TL;DR: In this paper, a new estimator is proposed for discrete choice models with choice-based sampling, which can incorporate information on the marginal choice probabilities in a straightforward manner and for that case leads to a procedure that is computationally and intuitively more appealing than the estimators that have been proposed before.
Estimation in generalized linear models for functional data via penalized likelihood
Hervé Cardot,Pacal Sarda +1 more
TL;DR: The functional coefficient of the model is estimated via penalized likelihood with spline approximation and the L2 rate of convergence of this estimator is given under smoothness assumption on the functional coefficient.
PLS classification of functional data
TL;DR: Partial least squares (PLS) as mentioned in this paper was proposed for linear discriminant analysis (LDA) when predictors are data of functional type (curves), based on the equivalence between LDA and the multiple linear regression (binary response) and LDA, and the canonical correlation analysis (more than two groups).
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Case-Control Studies
Ruth H. Keogh,David Cox +1 more
- 14 Apr 2014
TL;DR: This book covers the fundamentals of case-control study design and analysis as well as more recent developments, including two-stage studies, case-only studies and methods for case- control sampling in time.