Multiple linear regression model with stochastic design variables

DOI10.1080/02664760902939612OpenAlexW2032681665MaRDI QIDQ5123588

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Publication date: 29 September 2020

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664760902939612

zbMATH Keywords

least squarescorrelation coefficientmodified maximum likelihoodlinear regressionnon-normalityrandom designmultivariate distributions

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (5)

Modeling binary responses with stochastic covariates ⋮ Iterative weighted estimation based on variance modelling in linear regression models ⋮ Linear regression model with new symmetric distributed errors ⋮ Estimation in multivariate nonnormal distributions with stochastic variance function ⋮ Commentary on S. Kumar and P. Chhaparwal, 2016. A robust unbiased dual to product estimator for population mean through Modified Maximum Likelihood in simple random sampling, Cogent Mathematics, 3:1168070

Uses Software

• alr3

Cites Work

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• NONLINEAR DYNAMICAL SYSTEM IDENTIFICATION FROM UNCERTAIN AND INDIRECT MEASUREMENTS
• Regression Analysis with a Stochastic Design Variable
• A note on criterion robustness and inference robustness
• Estimation and hypothesis testing for a nonnormal bivariate distribution with applications
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