Modal linear regression using log-concave distributions-Reference-Cited by-同舟云学术

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Modal linear regression using log-concave distributions

Published:2020-10-10 Issue:2 Volume:50 Page:479-494
ISSN:1226-3192
Container-title:Journal of the Korean Statistical Society
language:en
Short-container-title:J. Korean Stat. Soc.

Author:

Kim Sunyul,Seo Byungtae^ORCID

Funder

National Research Foundation of Korea

Publisher

Springer Science and Business Media LLC

Subject

Statistics and Probability

Link

https://link.springer.com/content/pdf/10.1007/s42952-020-00089-y.pdf

Reference16 articles.

1. Chen, Y. C., Genovese, C. R., Tibshirani, R. J., & Wasserman, L. (2016). Nonparametric modal regression. The Annals of Statistics, 44(2), 489–514.

2. Dharmadhikari, S., & Joag-Dev, K. (1988). Unimodality, convexity, and applications. Amsterdam: Elsevier.

3. Doss, C. R., & Wellner, J. A. (2019). Univariate log-concave density estimation with symmetry or modal constraints. Electronic Journal of Statistics, 13(2), 2391–2461.

4. Dümbgen, L., & Rufibach, K. (2009). Maximum likelihood estimation of a log-concave density and its distribution function: Basic properties and uniform consistency. Bernoulli, 15(1), 40–68.

5. Dümbgen, L., & Rufibach, K. (2011). logcondens: Computations related to univariate log-concave density estimation. Journal of Statistical Software, 39(6), 1–28.

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Penalized maximum likelihood estimation with symmetric log-concave errors and LASSO penalty;Communications for Statistical Applications and Methods;2022-11-30

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