# Robust estimation of parameters in logistic regression via solving the Cramer-von Mises type L2 optimization problem

## TL;DR

This paper introduces a new method for estimating logistic regression parameters by solving a Cramer-von Mises type L2 optimization problem, with a thorough analysis of the estimators' asymptotic properties.

## Contribution

The paper presents a novel estimation approach for logistic regression parameters using a Cramer-von Mises type L2 optimization, advancing statistical estimation techniques.

## Key findings

- Establishes the asymptotic properties of the proposed estimators
- Demonstrates the effectiveness of the method through theoretical analysis
- Provides rigorous proofs of estimator consistency and asymptotic normality

## Abstract

This paper proposes a novel method to estimate parameters in a logistic regression model. After obtaining the estimators, their asymptotic properties are rigorously investigated.