Semiparametric and nonparametric methods in econometrics
Standard methods for estimating empirical models in economics and many other fields rely on strong assumptions about functional forms and the distributions of unobserved random variables. Often, it is assumed that functions of interest are linear or that unobserved random variables are normally dist...
Guardat en:
| Autor principal: | |
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| Format: | Livre numérique |
| Idioma: | Anglais |
| Publicat: |
New York, NY :
Springer New York
[20..].
Cham : Springer Nature |
| Edició: | 1st ed. 2009. |
| Col·lecció: | Springer Series in Statistics
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| Matèries: | |
| Accés en línia: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Nota: |
Description d'après consultation du 13 décembre 2011 Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Semiparametric and nonparametric methods in econometrics, Joel L. Horowitz, 2009, Dordrecht, Springer, 1 vol. (X-271 p.), Springer series in statistics, 978-0-387-92869-2 • Semiparametric and Nonparametric Methods in Econometrics, Texte imprimé, 9780387939254 • Semiparametric and nonparametric methods in econometrics, Joel L. Horowitz, 2009, Dordrecht, Springer, 1 vol. (X-271 p.), Springer series in statistics, 978-0-387-92869-2 • Semiparametric and nonparametric methods in econometrics, Joel L. Horowitz, 2009, Dordrecht, Springer, 1 vol. (X-271 p.), Springer series in statistics, 978-0-387-92869-2 • Semiparametric and Nonparametric Methods in Econometrics, Texte imprimé, 9780387939254 • Semiparametric and nonparametric methods in econometrics, Joel L. Horowitz, 2009, Dordrecht, Springer, 1 vol. (X-271 p.), Springer series in statistics, 978-0-387-92869-2 • Semiparametric and nonparametric methods in econometrics, Joel L. Horowitz, 2009, Dordrecht, Springer, 1 vol. (X-271 p.), Springer series in statistics, 978-0-387-92869-2 |
Taula de continguts:
- Single-Index Models Nonparametric Additive Models and Semiparametric Partially Linear Models Binary-Response Models Statistical Inverse Problems Transformation Models