Ziv-Zakai-type error bounds for general statistical models

06/14/2023
by   Mankei Tsang, et al.
0

I propose Ziv-Zakai-type lower bounds on the Bayesian error for estimating a parameter β:Θ→ℝ when the parameter space Θ is general and β(θ) need not be a linear function of θ.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
09/09/2016

Singularity structures and impacts on parameter estimation in finite mixtures of distributions

Singularities of a statistical model are the elements of the model's par...
research
03/06/2021

Over-the-Air Statistical Estimation

We study schemes and lower bounds for distributed minimax statistical es...
research
05/12/2019

Theoretical Limits of One-Shot Distributed Learning

We consider a distributed system of m machines and a server. Each machin...
research
05/07/2020

Lower bounds in multiple testing: A framework based on derandomized proxies

The large bulk of work in multiple testing has focused on specifying pro...
research
05/27/2019

Probabilistic mappings and Bayesian nonparametrics

In this paper we develop a functorial language of probabilistic mappings...
research
09/23/2020

An elementary approach for minimax estimation of Bernoulli proportion in the restricted parameter space

We present an elementary mathematical method to find the minimax estimat...
research
07/20/2022

Exploration of Parameter Spaces Assisted by Machine Learning

We showcase a variety of functions and classes that implement sampling p...

Please sign up or login with your details

Forgot password? Click here to reset