A Computational Framework for Multivariate Convex Regression and Its Variants-Reference-Cited by-同舟云学术

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A Computational Framework for Multivariate Convex Regression and Its Variants

Published:2018-08-15 Issue:525 Volume:114 Page:318-331
ISSN:0162-1459
Container-title:Journal of the American Statistical Association
language:en
Short-container-title:Journal of the American Statistical Association

Author:

Mazumder Rahul¹,Choudhury Arkopal²,Iyengar Garud³,Sen Bodhisattva⁴

Affiliation:

1. MIT Sloan School of Management, Massachusetts Institute of Technology, Cambridge, MA

2. Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC

3. IEOR Department, Columbia University, New York, NY

4. Department of Statistics, Columbia University, New York, NY

Publisher

Informa UK Limited

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/01621459.2017.1407771

Reference39 articles.

1. On uniform consistent estimators for convex regression

2. Nonparametric estimation of concave production technologies by entropic methods

3. A First-Order Augmented Lagrangian Method for Compressed Sensing

4. A parallel method for large scale convex regression problems

5. An Empirical Distribution Function for Sampling with Incomplete Information

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3. Plugin estimation of smooth optimal transport maps;The Annals of Statistics;2024-06-01

4. Estimating a Function and Its Derivatives Under a Smoothness Condition;Mathematics of Operations Research;2024-05-02

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