ramml {rpls} | R Documentation |
Robust Adaptive Modified Maximum Likelihood
Description
Modified Maximum Likelihood (MML) estimators are asymptotically equivalent to the ML estimators but their methodology works under the assumption of a known shape parameter. Robust Adaptive MML estimators weaken this assumption and are robust to vertical outliers as well as leverage points.
Usage
ramml(X,y,p,e)
Arguments
X |
predictor matrix |
y |
response variable |
p |
shape parameter of long-tailed symmetric distribution (considered as robustness tuning constant) |
e |
parameter for the linearization of the intractable term |
Value
coef |
vector of coefficients |
scale |
estimate of sigma |
fitted.values |
vector with fitted y-values |
residuals |
vector with y-residuals |
Author(s)
Sukru Acitas <sacitas@eskisehir.edu.tr>
References
S. Acitas, Robust Statistical Estimation Methods for High-Dimensional Data with Applications, tech. rep., TUBITAK 2219, International Post Doctoral Research Fellowship Programme, 2019.