A new robust parameter estimation approach for multinomial categorical response data with outliers and mismeasured covariates
From MaRDI portal
Publication:6164698
DOI10.1080/03610926.2022.2027447OpenAlexW4210488765MaRDI QIDQ6164698
Publication date: 28 July 2023
Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/03610926.2022.2027447
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- A new specification of generalized linear models for categorical responses
- Covariate measurement error in logistic regression
- Estimation in the polytomous logistic regression model
- A simple adjustment for measurement errors in some limited dependent variable models.
- Robust semiparametric inference for polytomous logistic regression with complex survey design
- Corrected score function for errors-in-variables models: Methodology and application to generalized linear models
- Calculation of Polychotomous Logistic Regression Parameters Using Individualized Regressions
- On the existence of maximum likelihood estimates in logistic regression models
- Unbiased estimation of a nonlinear function a normal mean with application to measurement err oorf models
- Asymptotic Statistics
- Robust Estimation for Grouped Data
- Consistent Functional Methods for Logistic Regression With Errors in Covariates
- Instrumental Variable Estimation in Binary Regression Measurement Error Models
- Parameter estimation approaches to tackling measurement error and multicollinearity in ordinal probit models
- Instrumental variable estimation in ordinal probit models with mismeasured predictors
- Instrument Assisted Regression for Errors in Variables Models with Binary Response
- Measurement Error in Nonlinear Models
- A Model for Quadratic Outliers in Linear Regression
- Generalized Wald-type tests based on minimum density power divergence estimators
- Robust inference with GMM estimators
This page was built for publication: A new robust parameter estimation approach for multinomial categorical response data with outliers and mismeasured covariates
