Optimal design for classification of functional data

2019 ◽  
Vol 48 (2) ◽  
pp. 285-307
Author(s):  
Cai Li ◽  
Luo Xiao
2018 ◽  
Vol 2 (334) ◽  
Author(s):  
Mirosław Krzyśko ◽  
Łukasz Smaga

In this paper, the binary classification problem of multi‑dimensional functional data is considered. To solve this problem a regression technique based on functional logistic regression model is used. This model is re‑expressed as a particular logistic regression model by using the basis expansions of functional coefficients and explanatory variables. Based on re‑expressed model, a classification rule is proposed. To handle with outlying observations, robust methods of estimation of unknown parameters are also considered. Numerical experiments suggest that the proposed methods may behave satisfactory in practice.


Test ◽  
2019 ◽  
Vol 29 (3) ◽  
pp. 637-660
Author(s):  
S. Barahona ◽  
P. Centella ◽  
X. Gual-Arnau ◽  
M. V. Ibáñez ◽  
A. Simó

Technometrics ◽  
2008 ◽  
Vol 50 (3) ◽  
pp. 284-294 ◽  
Author(s):  
Irene Epifanio

2007 ◽  
Vol 22 (2) ◽  
pp. 223-235 ◽  
Author(s):  
Cristian Preda ◽  
Gilbert Saporta ◽  
Caroline Lévéder
Keyword(s):  

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