Each week, we select a recently published Open Access article to feature. This week’s article comes from the Scandinavian Journal of Statistics and considers Grenander functionals and Cauchy’s formula.
The article’s abstract is given below, with the full article available to read here.
Grenander functionals and Cauchy’s formula. Scand J Statist. 2021; 48: 275– 294. https://doi.org/10.1111/sjos.12449.
Let f ^ n be the nonparametric maximum likelihood estimator of a decreasing density. Grenander characterized this as the left‐continuous slope of the least concave majorant of the empirical distribution function. For a sample from the uniform distribution, the asymptotic distribution of the L2‐distance of the Grenander estimator to the uniform density was derived in an article by Groeneboom and Pyke by using a representation of the Grenander estimator in terms of conditioned Poisson and gamma random variables. This representation was also used in an article by Groeneboom and Lopuhaä to prove a central limit result of Sparre Andersen on the number of jumps of the Grenander estimator. Here we extend this to the proof of the main result on the L2‐distance of the Grenander estimator to the uniform density and also prove a similar asymptotic normality results for the entropy functional. Cauchy’s formula and saddle point methods are the main tools in our development.