Regularized robust estimation in binary regression models. [PDF]
Tang Q, Karunamuni RJ, Liu B.
europepmc +1 more source
Modified maximum likelihood estimator under the Jones and Faddy's skew t-error distribution for censored regression model. [PDF]
Acitas S +3 more
europepmc +1 more source
Robust Statistical Inference in Generalized Linear Models Based on Minimum Renyi's Pseudodistance Estimators. [PDF]
Jaenada M, Pardo L.
europepmc +1 more source
Robust fitting of mixtures of GLMs by weighted likelihood. [PDF]
Greco L.
europepmc +1 more source
Network tomography based on 1-D projections
Network tomography has been regarded as one of the most promising methodologies for performance evaluation and diagnosis of the massive and decentralized Internet.
Cao, Jin, Chen, Aiyou
core +2 more sources
Trimmed Likelihood Estimation of the Parameters of the Generalized Extreme Value Distributions: a Monte-Carlo Study [PDF]
2000 Mathematics Subject Classification: Primary 62F35; Secondary 62P99The applicability of the Trimmed Likelihood Estimator (TLE) proposed by Neykov and Neytchev to the extreme value distributions is considered.
Dimova, Rositsa +2 more
core
An automatic robust Bayesian approach to principal component regression. [PDF]
Gagnon P, Bédard M, Desgagné A.
europepmc +1 more source
Multiresponse Robust Engineering: Case with Errors in Factor Levels [PDF]
2000 Mathematics Subject Classification: 62J05, 62J10, 62F35, 62H12, 62P30.The model-based robust approach for improving the quality of the process is successfully applied to different industrial processes.
Koleva, Elena +2 more
core
High breakdown estimators for principal components: the projection-pursuit approach revisited. [PDF]
Li and Chen (J. Amer. Statist. Assoc. 80 (1985) 759) proposed a method for principal components using projection-pursuit techniques. In classical principal components one searches for directions with maximal variance, and their approach consists of ...
Croux, Christophe, Ruiz-Gazen, A
core
Variable selection in finite mixture of regression models using the skew-normal distribution. [PDF]
Yin J, Wu L, Dai L.
europepmc +1 more source

