Smooth Distribution Function Estimation for Lifetime Distributions using Szasz-Mirakyan Operators

05/20/2020
by   Ariane Hanebeck, et al.
0

In this paper, we introduce a new smooth estimator for continuous distribution functions on the positive real half-line using Szasz-Mirakyan Operators. The approach is similar to the idea of the Bernstein estimator. We show that the proposed estimator outperforms the empirical distribution function in terms of asymptotic (integrated) mean-squared error, and generally compares favourably with other competitors in theoretical comparisons and in a simulation study.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
12/03/2019

Mean-shift least squares model averaging

This paper proposes a new estimator for selecting weights to average ove...
research
10/03/2019

Exploring Positive Noise in Estimation Theory

Estimation of a deterministic quantity observed in non-Gaussian additive...
research
02/11/2022

POT-flavored estimator of Pickands dependence function

This work proposes an estimator with both Peak-Over-Threshold and Block-...
research
10/14/2021

Kernel estimation for the tail index of a right-censored Pareto-type distribution

We introduce a kernel estimator, to the tail index of a right-censored P...
research
11/05/2019

The correlation-assisted missing data estimator

We introduce a novel approach to estimation problems in settings with mi...
research
12/20/2017

Estimating historic movement of a climatological variable from a pair of misaligned data sets

We consider in this paper the problem of estimating the mean function fr...
research
12/06/2019

Risk-Aware MMSE Estimation

Despite the simplicity and intuitive interpretation of Minimum Mean Squa...

Please sign up or login with your details

Forgot password? Click here to reset