Deconvolution;
McKean-Vlasov SDEs;
Mean field models;
Multi-agent learning;
Minimax bounds;
Semiparametric estimation;
GRANULAR MEDIA EQUATIONS;
D O I:
10.1214/22-AIHP1261
中图分类号:
O21 [概率论与数理统计];
C8 [统计学];
学科分类号:
020208 ;
070103 ;
0714 ;
摘要:
In this paper we study the problem of semiparametric estimation for a class of McKean-Vlasov stochastic differential equations. Our aim is to estimate the drift coefficient of a MV-SDE based on observations of the corresponding particle system. We propose a semiparametric estimation procedure and derive the rates of convergence for the resulting estimator. We further prove that the obtained rates are essentially optimal in the minimax sense.
机构:
Univ Pompeu Fabra, Barcelona Sch Econ, Ramon Trias Fargas 25-27, Barcelona 08005, SpainUniv Pompeu Fabra, Barcelona Sch Econ, Ramon Trias Fargas 25-27, Barcelona 08005, Spain
Amorino, Chiara
Belomestny, Denis
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机构:
Dusiburg Essen Univ, Dept Math, Thea Leymann Str 9, D-45127 Essen, GermanyUniv Pompeu Fabra, Barcelona Sch Econ, Ramon Trias Fargas 25-27, Barcelona 08005, Spain
Belomestny, Denis
Pilipauskaite, Vytaute
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机构:
Aalborg Univ, Dept Math Sci, Thomas Manns Vej 23, DK-9220 Aalborg, DenmarkUniv Pompeu Fabra, Barcelona Sch Econ, Ramon Trias Fargas 25-27, Barcelona 08005, Spain
Pilipauskaite, Vytaute
Podolskij, Mark
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机构:
Univ Luxembourg, Dept Math, 6 Ave Fonte, L-4364 Esch Sur Alzette, LuxembourgUniv Pompeu Fabra, Barcelona Sch Econ, Ramon Trias Fargas 25-27, Barcelona 08005, Spain
Podolskij, Mark
Zhou, Shi-Yuan
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机构:
Univ Luxembourg, Dept Math, 6 Ave Fonte, L-4364 Esch Sur Alzette, LuxembourgUniv Pompeu Fabra, Barcelona Sch Econ, Ramon Trias Fargas 25-27, Barcelona 08005, Spain