Robust mixture regression modeling based on the generalized M (GM)-estimation method
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Publication:5082728
DOI10.1080/03610918.2019.1610442zbMath1497.62073arXiv1511.07384OpenAlexW2964173314MaRDI QIDQ5082728
Fatma Zehra Dogru, Olcay Arslan
Publication date: 21 June 2022
Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1511.07384
Computational methods for problems pertaining to statistics (62-08) Linear regression; mixed models (62J05) Point estimation (62F10) Robustness and adaptive procedures (parametric inference) (62F35)
Uses Software
Cites Work
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- Robust fitting of mixtures using the trimmed likelihood estimator
- Robust fitting of mixture regression models
- Robust mixture regression model fitting by Laplace distribution
- A profile likelihood method for normal mixture with unequal variance
- Robust estimation of mixtures of regressions with random covariates, via trimming and constraints
- High breakdown-point and high efficiency robust estimates for regression
- A constrained formulation of maximum-likelihood estimation for normal mixture distributions
- Clusterwise linear regression
- Standard errors of fitted component means of normal mixture
- Identifiability of models for clusterwise linear regression
- Robust mixture regression using the \(t\)-distribution
- Robust regression: Asymptotics, conjectures and Monte Carlo
- Finite mixture and Markov switching models.
- Robust Mixture of Linear Regression Models
- Asymptotic behavior of general M-estimates for regression and scale with random carriers
- Estimation in Linear Regression Models with Disparate Data Points
- Efficient Bounded-Influence Regression Estimation
- On One-Step GM Estimates and Stability of Inferences in Linear Regression
- A Robust Method for Multiple Linear Regression
- Estimating Mixtures of Normal Distributions and Switching Regressions
- Smoothing Parameter Selection in Nonparametric Regression Using an Improved Akaike Information Criterion
- Local Regression and Likelihood
- Mixed Poisson Regression Models with Covariate Dependent Rates
- Parameter estimation for mixtures of skew Laplace normal distributions and application in mixture regression modeling
- Distributions Generated by Perturbation of Symmetry with Emphasis on a Multivariate Skewt-Distribution
- Mixture Models, Robustness, and the Weighted Likelihood Methodology
- Robust mixture regression based on the skew t distribution
- Robust Statistics
- A New Approach to Estimating Switching Regressions
- Robust Statistics
- Robust Statistics
