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A robust Liu regression estimator
Communications in Statistics - Simulation and Computation, 2017The least-squares regression estimator can be very sensitive in the presence of multicollinearity and outliers in the data. We introduce a new robust estimator based on the MM estimator.
Peter Filzmoser, Fatma Sevinç Kurnaz
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Robust Estimation and Robust Parameter
2020This chapter is addressed to the problem of defining the parameter in a semiparametric situation. Suppose, for example, that the observation X is assumed to be expressed as \(X=\theta +\varepsilon \), where \(\theta \) is the parameter to be estimated and \(\varepsilon \) is the error whose distribution is not specified by a finite number of parameters.
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Robust estimation for circular data
Computational Statistics & Data Analysis, 2007zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Minimum Distance and Robust Estimation
Journal of the American Statistical Association, 1980William C Parr, William R Schucany
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Robust Estimation of the First-Order Autoregressive Parameter
Journal of the American Statistical Association, 1979R Douglas Martin
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Robust Sets of Regression Estimates
Econometrica, 1983Gilstein, C Zachary, Leamer, Edward E
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A Comparison of Diagonal Weighted Least Squares Robust Estimation Techniques for Ordinal Data
Structural Equation Modeling, 2014Christine Distefano, Grant B Morgan
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