Shrinkage estimation of rate statistics

10/17/2018
by   Einar Holsbø, et al.
0

This paper presents a simple shrinkage estimator of rates based on Bayesian methods. Our focus is on crime rates as a motivating example. The estimator shrinks each town's observed crime rate toward the country-wide average crime rate according to town size. By realistic simulations we confirm that the proposed estimator outperforms the maximum likelihood estimator in terms of global risk. We also show that it has better coverage properties.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
06/07/2023

Non-minimaxity of debiased shrinkage estimators

We consider the estimation of the p-variate normal mean of X∼ N_p(θ,I) u...
research
07/29/2021

Polynomials shrinkage estimators of a multivariate normal mean

In this work, the estimation of the multivariate normal mean by differen...
research
12/15/2022

An estimator for the recombination rate from a continuously observed diffusion of haplotype frequencies

Recombination is a fundamental evolutionary force, but it is difficult t...
research
06/22/2020

C-SURE: Shrinkage Estimator and Prototype Classifier for Complex-Valued Deep Learning

The James-Stein (JS) shrinkage estimator is a biased estimator that capt...
research
07/26/2019

On the variability of regression shrinkage methods for clinical prediction models: simulation study on predictive performance

When developing risk prediction models, shrinkage methods are recommende...
research
06/02/2022

Likelihood-based Instrumental Variable Methods for Cox Proportional Hazard Models

In biometrics and related fields, the Cox proportional hazards model are...
research
09/28/2020

Shrinkage Estimation of the Frechet Mean in Lie groups

Data in non-Euclidean spaces are commonly encountered in many fields of ...

Please sign up or login with your details

Forgot password? Click here to reset