FUNCTIONAL RESPONSE MODELS
By Jeng-Min Chiou, H. Muller, Jane-ling Wang. 2004
140 citations recorded by the source corpus.
View Paper: https://www.semanticscholar.org/paper/8060b8464236c0c516767db25ea277c99eb00ef7
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Citations in the corpus
- Functional Modelling and Classification of Longitudinal Data * (2005, background): “Response Model Rd R Multiple Regression, GLM Rd Rd Multivariate Regression L2 L2 ‘Functional Regression Model’ Rd L2 ‘Functional Response Model’ L2 R ‘Generalized Functional Linear Model’ Board of the Foundation of the Scandinavian Journal of Statistics 2005.”
- Functional data analysis for volatility (2011, background): “Among these are Faraway (1997) and Chiou et al. (2004), where in both approaches predictors are vector-valued.”
- Operator-valued Kernels for Learning from Functional Response Data (2015, background): “A review of functional response models can be found in Chiou et al. (2004).”
- Asymptotics of prediction in functional linear regression with functional outputs (2009, methodology): “Though distinct, this estimate remains close from the one proposed in Yao, Müller and Wang [23], the difference consisting in the fact that we do not consider a Karhunen–Loeve development of Y .”
- Weakly dependent functional data (2010, background): “Indicating with the “hat” the corresponding empirical quantities, an estimator of ψ(t, s) proposed by Yao, Müller and Wang [65] is ψ̂KL(t, s) = K∑ k=1 L∑ =1 λ̂−1 σ̂ kûk(t)v̂ (s), where σ̂ k is an estimator of E[ξ ζk].”
- Electricity consumption prediction with functional linear regression using spline estimators (2010, background): “However, concerning identifiability of the model (existence and uniqueness of the function parameter β2), condition given in [5] (see also [14]) still holds here, whereas we conjecture that the good asymptotic behaviour of the B-spline estimator defined below remains valid for this kind of weak depe”