Translator Disclaimer
November 2018 Some Developments in the Theory of Shape Constrained Inference
Piet Groeneboom, Geurt Jongbloed
Statist. Sci. 33(4): 473-492 (November 2018). DOI: 10.1214/18-STS657

Abstract

Shape constraints enter in many statistical models. Sometimes these constraints emerge naturally from the origin of the data. In other situations, they are used to replace parametric models by more versatile models retaining qualitative shape properties of the parametric model. In this paper, we sketch a part of the history of shape constrained statistical inference in a nutshell, using landmark results obtained in this area. For this, we mainly use the prototypical problems of estimating a decreasing probability density on $[0,\infty )$ and the estimation of a distribution function based on current status data as illustrations.

Citation

Download Citation

Piet Groeneboom. Geurt Jongbloed. "Some Developments in the Theory of Shape Constrained Inference." Statist. Sci. 33 (4) 473 - 492, November 2018. https://doi.org/10.1214/18-STS657

Information

Published: November 2018
First available in Project Euclid: 29 November 2018

zbMATH: 07032825
MathSciNet: MR3881204
Digital Object Identifier: 10.1214/18-STS657

Rights: Copyright © 2018 Institute of Mathematical Statistics

JOURNAL ARTICLE
20 PAGES

This article is only available to subscribers.
It is not available for individual sale.
+ SAVE TO MY LIBRARY

SHARE
Vol.33 • No. 4 • November 2018
Back to Top