Some developments in the theory of shape constrained inference. (English) Zbl 1407.62108

Summary: 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.


62G05 Nonparametric estimation
62N01 Censored data models
Full Text: DOI Euclid


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