A refined continuity correction for the negative binomial distribution and asymptotics of the median

03/16/2021
by   Frédéric Ouimet, et al.
0

In this paper, we prove a local limit theorem and a refined continuity correction for the negative binomial distribution. We present two applications of the results. First, we find the asymptotics of the median for a Negative Binomial (r,p) random variable jittered by a Uniform (0,1), which answers a problem left open in Coeurjolly & Trépanier (2020). This is used to construct a simple, robust and consistent estimator of the parameter p, when r > 0 is known. Second, we find an upper bound on the Le Cam distance between negative binomial and normal experiments.

READ FULL TEXT
research
10/29/2020

A non-asymptotic version of Cressie's refined continuity correction for the binomial distribution

In this paper, we prove a non-asymptotic version of the refined continui...
research
08/06/2023

Asymptotic comparison of negative multinomial and multivariate normal experiments

This note presents a refined local approximation for the logarithm of th...
research
01/19/2022

Refined normal approximations for the central and noncentral chi-square distributions and some applications

In this paper, we prove a local limit theorem for the chi-square distrib...
research
01/23/2020

A precise local limit theorem for the multinomial distribution

We develop a precise local limit theorem for the multinomial distributio...
research
01/16/2019

The median of a jittered Poisson distribution

Let N_λ and U be two independent random variables respectively distribut...
research
02/22/2023

The Power of Uniform Sampling for k-Median

We study the power of uniform sampling for k-Median in various metric sp...
research
04/14/2020

Uniform preconditioners of linear complexity for problems of negative order

We propose a multi-level type operator that can be used in the framework...

Please sign up or login with your details

Forgot password? Click here to reset