Jean-Pierre Florens – författare
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5 produkter
Econometric Modeling and Inference
Av Jean-Pierre Florens, Velayoudom Marimoutou m. fl.
Häftad, 2007
838 kr
Lägg i varukorg
Presents the main statistical tools of econometrics, focusing specifically on modern econometric methodology. The authors unify the approach by using a small number of estimation techniques, mainly generalized method of moments (GMM) estimation and kernel smoothing. The choice of GMM is explained …
Nonparametric Bayesian Inference
Contributions by Jean-Marie Rolin
Av Jean-Pierre Florens, Michel Mouchart
Inbunden, 2024
2401 kr
Lägg i varukorg
This book is a compilation of unpublished papers written by Jean-Marie Rolin (with several co-authors) on nonparametric bayesian estimation. Jean-Marie was professor of statistics at University of Louvain and died on November 5th, 2018. He made important contributions in mathematical statistics …
Nonparametric Bayesian Inference
Contributions by Jean-Marie Rolin
Av Michel Mouchart, Jean-Pierre Florens
E-bok, 2024
3251 kr
Lägg i varukorg
This book is a compilation of unpublished papers written by Jean-Marie Rolin (with several co-authors) on nonparametric bayesian estimation. Jean-Marie was professor of statistics at University of Louvain and died on November 5th, 2018. He made important contributions in mathematical statistics …
Nonparametric Bayesian Inference
Contributions by Jean-Marie Rolin
Av Jean-Pierre Florens, Michel Mouchart
Häftad, 2025
2510 kr
Lägg i varukorg
This book is a compilation of unpublished papers written by Jean-Marie Rolin (with several co-authors) on nonparametric bayesian estimation. Jean-Marie was professor of statistics at University of Louvain and died on November 5th, 2018. He made important contributions in mathematical statistics …
Econometric Modeling and Inference
Av Jean-Pierre Florens, Velayoudom Marimoutou m. fl.
Inbunden, 2007
1118 kr
Tillfälligt slut
Presents the main statistical tools of econometrics, focusing specifically on modern econometric methodology. The authors unify the approach by using a small number of estimation techniques, mainly generalized method of moments (GMM) estimation and kernel smoothing. The choice of GMM is explained …
