✦ LIBER ✦

A robust method of estimation based on the MML estimators for a single linear regression model

✍ Scribed by N. Balakrishnan; R.S. Ambagaspitiya

Publisher: Elsevier Science
Year: 1992
Tongue: English
Weight: 736 KB
Volume: 30
Category: Article
ISSN: 0378-3758
DOI: 10.1016/0378-3758(92)90087-9

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Robust estimation for the Cox regression

Robust estimation for the Cox regression model based on trimming

✍ Alessio Farcomeni; Sara Viviani 📂 Article 📅 2011 🏛 John Wiley and Sons 🌐 English ⚖ 231 KB 👁 2 views

## Abstract We propose a robust Cox regression model with outliers. The model is fit by trimming the smallest contributions to the partial likelihood. To do so, we implement a Metropolis‐type maximization routine, and show its convergence to a global optimum. We discuss global robustness properties

A New Class of Consistent Estimators for

A New Class of Consistent Estimators for Stochastic Linear Regressive Models

✍ Hong-Zhi An; Fred J Hickernell; Li-Xing Zhu 📂 Article 📅 1997 🏛 Elsevier Science 🌐 English ⚖ 349 KB

In this paper we propose a new approach for estimating the unknown parameter in the stochastic linear regressive model with stationary ergodic sequence of covariates. Under mild conditions on the joint distribution of the covariate and the error, the estimator constructed is shown to be strongly con

Improved estimation of the disturbance v

Improved estimation of the disturbance variance in a linear regression model

✍ Alan E. Gelfand; Dipak K. Dey 📂 Article 📅 1988 🏛 Elsevier Science 🌐 English ⚖ 456 KB

Estimation of a Conditional Mean in a Li

Estimation of a Conditional Mean in a Linear Regression Model after a Preliminary Test on Regression Coefficient

✍ Dinesh S. Bhoj; Mohammad Ahsanullah 📂 Article 📅 1994 🏛 John Wiley and Sons 🌐 English ⚖ 449 KB 👁 2 views

## Abstract Consider the two linear regression models of __Y__~__ij__~ on __X__~__ij__~, namely __Y__~__ij__~ = β~__io__~ + β~__ij__~, __X__~__ij__~ + __E__~__ij__~ = 1, 2,…, __n__~__i__~, __i__ = 1, 2, where __E__~__ij__~ are assumed to be normally distributed with zero mean and common unknown var

Efficiency and Robustness of a Resamplin

Efficiency and Robustness of a Resampling M-Estimator in the Linear Model

✍ Feifang Hu 📂 Article 📅 2001 🏛 Elsevier Science 🌐 English ⚖ 156 KB

In the literature, there are basically two kinds of resampling methods for least squares estimation in linear models; the E-type (the efficient ones like the classical bootstrap), which is more efficient when error variables are homogeneous, and the R-type (the robust ones like the jackknife), which

Parametric empirical Bayes estimation fo

Parametric empirical Bayes estimation for a class of extended log-linear regression models

✍ Wanzhu Tu; Walter W. Piegorsch 📂 Article 📅 2000 🏛 John Wiley and Sons 🌐 English ⚖ 155 KB 👁 3 views

This paper presents a fully parametric empirical Bayes approach for the analysis of count data, with emphasis on its application to environmental toxicity data. A hierarchical structure for the mean response is developed from a generalized linear model, based on a Poisson distribution. The linear pr