We consider the smoothed version of sliced average variance estimation (SAVE) dimension reduction method for dealing with spatially dependent data that are observations of a strongly mixing random field. We propose kernel estimators for the interest matrix and the effective dimension reduction (EDR) space, and show their consistency.
Nous considérons la version lisse de la méthode SAVE pour prendre en compte des observations spatialement dépendantes émanant d’un champ aléatoire fortement mélangeant. Nous proposons des estimateurs à noyau pour la matrice d’intérêt et l’espace de rédution de la dimension, et montrons leur convergence.
Accepted:
Published online:
DOI: 10.5802/crmath.187
@article{CRMATH_2021__359_4_475_0, author = {Affossogbe, M\`etolidji Moquilas Raymond and Nkiet, Guy Martial and Ogouyandjou, Carlos}, title = {Dimension reduction in spatial regression with kernel {SAVE} method}, journal = {Comptes Rendus. Math\'ematique}, pages = {475--479}, publisher = {Acad\'emie des sciences, Paris}, volume = {359}, number = {4}, year = {2021}, doi = {10.5802/crmath.187}, zbl = {07362167}, language = {en}, url = {http://archive.numdam.org/articles/10.5802/crmath.187/} }
TY - JOUR AU - Affossogbe, Mètolidji Moquilas Raymond AU - Nkiet, Guy Martial AU - Ogouyandjou, Carlos TI - Dimension reduction in spatial regression with kernel SAVE method JO - Comptes Rendus. Mathématique PY - 2021 SP - 475 EP - 479 VL - 359 IS - 4 PB - Académie des sciences, Paris UR - http://archive.numdam.org/articles/10.5802/crmath.187/ DO - 10.5802/crmath.187 LA - en ID - CRMATH_2021__359_4_475_0 ER -
%0 Journal Article %A Affossogbe, Mètolidji Moquilas Raymond %A Nkiet, Guy Martial %A Ogouyandjou, Carlos %T Dimension reduction in spatial regression with kernel SAVE method %J Comptes Rendus. Mathématique %D 2021 %P 475-479 %V 359 %N 4 %I Académie des sciences, Paris %U http://archive.numdam.org/articles/10.5802/crmath.187/ %R 10.5802/crmath.187 %G en %F CRMATH_2021__359_4_475_0
Affossogbe, Mètolidji Moquilas Raymond; Nkiet, Guy Martial; Ogouyandjou, Carlos. Dimension reduction in spatial regression with kernel SAVE method. Comptes Rendus. Mathématique, Volume 359 (2021) no. 4, pp. 475-479. doi : 10.5802/crmath.187. http://archive.numdam.org/articles/10.5802/crmath.187/
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