Regression Analysis with a Stochastic Design Variable

DOI10.1111/J.1751-5823.2006.TB00162.XzbMath1131.62060OpenAlexW2061360988MaRDI QIDQ5446542

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Publication date: 6 March 2008

Published in: International Statistical Review (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/j.1751-5823.2006.tb00162.x

zbMATH Keywords

least squarescorrelation coefficientnon-normalitymodified likelihood

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Parametric hypothesis testing (62F03) Point estimation (62F10) General nonlinear regression (62J02)

Related Items (12)

The modified maximum likelihood estimators for the parameters of the regression model under bivariate median ranked set sampling ⋮ The modified maximum likelihood regression type estimators using bivariate ranked set sampling ⋮ Comparison of the robust methods in the general linear regression model ⋮ Multiple linear regression model with stochastic design variables ⋮ Inference in multivariate linear regression models with elliptically distributed errors ⋮ Stochastic analysis of covariance when the error distribution is long-tailed symmetric ⋮ Application in stochastic volatility models of nonlinear regression with stochastic design ⋮ Mahalanobis distance under non-normality ⋮ Estimation in multivariate nonnormal distributions with stochastic variance function ⋮ Robust Estimation and Hypothesis Testing of Linear Contrasts in Analysis of Covariance with Stochastic Covariates ⋮ Estimation in bivariate nonnormal distributions with stochastic variance functions ⋮ A note on the paper by Ahmed Hossain and Andrew R. Willan

Cites Work

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• Modified maximum likelihood method for the robust estimation of system parameters from very noisy data
• A new method of estimation for location and scale parameters
• The Asymptotics of Maximum Likelihood and Related Estimators Based on Type II Censored Data
• On estimating the scale parameter of the Rayleigh distribution from doubly censored samples
• Logistic and Nonlogistic Density Functions in Binary Regression with Nonstochastic Covariates
• Evaluation of the maximum-likelihood estimator where the likelihood equation has multiple roots
• THE FREQUENCY DISTRIBUTION OF THE PRODUCT-MOMENT CORRELATION COEFFICIENT IN RANDOM SAMPLES OF ANY SIZE DRAWN FROM NON-NORMAL UNIVERSES
• Estimation and hypothesis testing for a nonnormal bivariate distribution with applications

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