Stacked Grenander and rearrangement estimators of a discrete distribution

06/01/2021
by   Vladimir Pastukhov, et al.
0

In this paper we consider the stacking of isotonic regression and the method of rearrangement with the empirical estimator to estimate a discrete distribution with an infinite support. The estimators are proved to be strongly consistent with √(n)-rate of convergence. We obtain the asymptotic distributions of the estimators and construct the asymptotically correct conservative global confidence bands. We show that stacked Grenander estimator outperforms the stacked rearrangement estimator. The new estimators behave well even for small sized data sets and provide a trade-off between goodness-of-fit and shape constraints.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
10/19/2022

Constrained estimation of a discrete distribution with probabilistic forecast control

In this paper we integrate the isotonic regression with Stone's cross-va...
research
08/20/2019

Results on standard estimators in the Cox model

We consider the Cox regression model and prove some properties of the ma...
research
09/18/2023

Error Reduction from Stacked Regressions

Stacking regressions is an ensemble technique that forms linear combinat...
research
06/15/2009

Maximal digital straight segments and convergence of discrete geometric estimators

Discrete geometric estimators approach geometric quantities on digitized...
research
03/21/2018

Network and Panel Quantile Effects Via Distribution Regression

This paper provides a method to construct simultaneous confidence bands ...
research
11/10/2019

Optimal robust estimators for families of distributions on the integers

Let F_θ be a family of distributions with support on the set of nonnegat...
research
05/30/2021

The HulC: Confidence Regions from Convex Hulls

We develop and analyze the HulC, an intuitive and general method for con...

Please sign up or login with your details

Forgot password? Click here to reset