Minimum mean-squared error estimation in linear regression with an inequality constraint
- Author
- WAN, A. T. K1 ; OHTANI, K2
[1] Department of Management Sciences, City University of Hong Kong, Kowloon, Hong-Kong
[2] Faculty of Economics, Kobe University, Rokko, Nadu-ku, Kobe 657, Japan - Source
Journal of statistical planning and inference. 2000, Vol 86, Num 1, pp 157-173 ; ref : 26 ref
- CODEN
- JSPIDN
- ISSN
- 0378-3758
- Scientific domain
- Control theory, operational research; Computer science; Mathematics
- Publisher
- Elsevier Science, Amsterdam
/
Elsevier Science, Lausanne
/
Elsevier Science, New York,NY
- Publication country
- Netherlands
- Document type
- Article
- Language
- English
- Keyword (fr)
- Condition suffisante Contrainte inégalité Erreur quadratique moyenne Optimisation sous contrainte Régression linéaire FMMSE estimator MMSE estimator Perte quadratique Règle Stein
- Keyword (en)
- Sufficient condition Inequality constraint Mean square error Constrained optimization Linear regression Feasible minimum mean squared estimator Minimum mean squared estimator Quadratic loss Stein rule
- Keyword (es)
- Condición suficiente Constreñimiento desigualdad Error medio cuadrático Optimización con restricción Regresión lineal
- Classification
- Pascal
- 001 Exact sciences and technology / 001A Sciences and techniques of general use / 001A02 Mathematics / 001A02H Probability and statistics / 001A02H02 Statistics / 001A02H02J Linear inference, regression
- Discipline
- Mathematics
- Origin
- Inist-CNRS
- Database
- PASCAL
- INIST identifier
- 1298544
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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DOI
10.1016/S0378-3758(99)00172-X 
https://dx.doi.org/10.1016/S0378-3758(99)00172-X
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