Add to ORKGWe propose a least median of absolute (LMA) estimator for a linear regression model, based on minimizing the median absolute deviation of the residuals. Under some regularity conditions on the design points and disturbances, the strong convergence rate of the LMA estimator is established.Statistics & ProbabilitySCI(E)0ARTICLE2183-2014
AbstractThe rate of convergence of the least squares estimator in a non-linear regression model with...
This paper proposes an alternative to maximum likelihood estimation of the parameters of the censore...
We consider the consistency and weak convergence of $S$-estimators in the linear regression model. S...
linear regression, median absolute deviation, strong convergence rate, LMA estimator, 62J05, 62F12,
The LAD estimator of the vector parameter in a linear regression is defined by minimizing the sum of...
We consider an L_1 analogue of the least squares estimate or for the parameters of stationary, finit...
For its simplicity and elegant theoretical properties, Least Squares (LS) regression has been used a...
This is a theoretical study of the Least Absolute Deviations (LAD) fits. In the first part, fundamen...
Least absolute deviation (LAD) regression is an important tool used in numerous applications through...
We consider a simple through-the-origin linear regression example introduced by Rousseeuw, van Aelst...
Classical least squares regression consists of minimizing the sum of the squared residuals. Many aut...
Algorithm for the exact solution of the problem of estimating the parameters of linear regression mo...
We propose a least absolute deviation estimation method that produced a least absolute deviation est...
Given a dataset an outlier can be defined as an observation that does not follow the statistical pro...
Consider the partly Linear model Y-i = X(i)'beta(0)+g(0)(T-i)+e(i), where {((Ti, X(i))}(infinit...
AbstractThe rate of convergence of the least squares estimator in a non-linear regression model with...
This paper proposes an alternative to maximum likelihood estimation of the parameters of the censore...
We consider the consistency and weak convergence of $S$-estimators in the linear regression model. S...
linear regression, median absolute deviation, strong convergence rate, LMA estimator, 62J05, 62F12,
The LAD estimator of the vector parameter in a linear regression is defined by minimizing the sum of...
We consider an L_1 analogue of the least squares estimate or for the parameters of stationary, finit...
For its simplicity and elegant theoretical properties, Least Squares (LS) regression has been used a...
This is a theoretical study of the Least Absolute Deviations (LAD) fits. In the first part, fundamen...
Least absolute deviation (LAD) regression is an important tool used in numerous applications through...
We consider a simple through-the-origin linear regression example introduced by Rousseeuw, van Aelst...
Classical least squares regression consists of minimizing the sum of the squared residuals. Many aut...
Algorithm for the exact solution of the problem of estimating the parameters of linear regression mo...
We propose a least absolute deviation estimation method that produced a least absolute deviation est...
Given a dataset an outlier can be defined as an observation that does not follow the statistical pro...
Consider the partly Linear model Y-i = X(i)'beta(0)+g(0)(T-i)+e(i), where {((Ti, X(i))}(infinit...
AbstractThe rate of convergence of the least squares estimator in a non-linear regression model with...
This paper proposes an alternative to maximum likelihood estimation of the parameters of the censore...
We consider the consistency and weak convergence of $S$-estimators in the linear regression model. S...