From ε-entropy to KL-entropy : Analysis of minimum information complexity density estimation
- Author
- TONG ZHANG1
[1] Yahoo Research, United States - Source
Annals of statistics. 2006, Vol 34, Num 5, pp 2180-2210, 31 p ; ref : 18 ref
- CODEN
- ASTSC7
- ISSN
- 0090-5364
- Scientific domain
- Mathematics
- Publisher
- Institute of Mathematical Statistics, Hayward, CA
- Publication country
- United States
- Document type
- Article
- Language
- English
- Keyword (fr)
- Convergence Divergence Entropie Estimation Bayes Estimation densité Loi a posteriori Mesure complexité Méthode statistique Théorie information
- Keyword (en)
- Convergence Divergence Entropy Bayes estimation Density estimation Posterior distribution Complexity measure Statistical method Information theory
- Keyword (es)
- Convergencia Divergencia Entropía Estimación Bayes Estimación densidad Ley a posteriori Medida complexidad Método estadístico Teoría información
- Classification
- Pascal
- 001 Exact sciences and technology / 001A Sciences and techniques of general use / 001A02 Mathematics / 001A02H Probability and statistics / 001A02H02 Statistics / 001A02H02C Sufficiency and information
- Pascal
- 001 Exact sciences and technology / 001A Sciences and techniques of general use / 001A02 Mathematics / 001A02H Probability and statistics / 001A02H02 Statistics / 001A02H02H Nonparametric inference
- Discipline
- Mathematics
- Origin
- Inist-CNRS
- Database
- PASCAL
- INIST identifier
- 18518887
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
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