Estimating a Convex Function in Nonparametric Regression
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References listed on IDEAS
- Dette, Holger & Birke, Melanie, 2005. "A note on estimating a monotone regression by combining kernel and density estimates," Technical Reports 2005,24, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
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- Leorato, S., 2009.
"A refined Jensen's inequality in Hilbert spaces and empirical approximations,"
Journal of Multivariate Analysis,
Elsevier, vol. 100(5), pages 1044-1060, May.
- Samantha Leorato, 2008. "A refined Jensen’s inequality in Hilbert spaces and empirical approximations," CEIS Research Paper 134, Tor Vergata University, CEIS, revised 24 Nov 2008.
- Wang, J. & Ghosh, S.K., 2012. "Shape restricted nonparametric regression with Bernstein polynomials," Computational Statistics & Data Analysis, Elsevier, vol. 56(9), pages 2729-2741.
- Blundell, Richard & Kristensen, Dennis & Matzkin, Rosa, 2014.
"Bounding quantile demand functions using revealed preference inequalities,"
Journal of Econometrics,
Elsevier, vol. 179(2), pages 112-127.
- Richard Blundell & Dennis Kristensen & Rosa Matzkin, 2011. "Bounding quantile demand functions using revealed preference inequalities," CeMMAP working papers CWP21/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Keshvari, Abolfazl, 2017. "A penalized method for multivariate concave least squares with application to productivity analysis," European Journal of Operational Research, Elsevier, vol. 257(3), pages 1016-1029.
- Dentcheva, Darinka & Penev, Spiridon, 2010. "Shape-restricted inference for Lorenz curves using duality theory," Statistics & Probability Letters, Elsevier, vol. 80(5-6), pages 403-412, March.
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