Modified likelihood ratio tests in heteroskedastic multivariate regression models with measurement error
DOI10.1080/00949655.2013.787691zbMath1453.62570arXiv1205.5039OpenAlexW1982415000WikidataQ57496471 ScholiaQ57496471MaRDI QIDQ5219488
Alexandre G. Patriota, Tatiane F. N. Melo, Silvia L. P. Ferrari
Publication date: 12 March 2020
Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1205.5039
measurement errorelliptical distributionmultivariate regression modelerrors-in-variables modelmodified likelihood ratio statistic
Linear regression; mixed models (62J05) Applications of statistics to biology and medical sciences; meta analysis (62P10) Asymptotic properties of parametric tests (62F05)
Related Items (2)
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- On estimation of a heteroscedastic measurement error model under heavy-tailed distributions
- Improved maximum likelihood estimators in a heteroskedastic errors-in-variables model
- A heteroscedastic structural errors-in-variables model with equation error
- Multivariate elliptical models with general parameterization
- Decomposition and invariance of measures, and statistical transformation models
- On the maximum likelihood estimation of a linear structural relationship when the intercept is known
- A modified signed likelihood ratio test in elliptical structural models
- Null intercept measurement error regression models
- Likelihood Asymptotics
- Measurement Error
- Modified signed log likelihood ratio
- Likelihood estimation of a simple linear regression model when both variables have error
- Robustness of the student t based M-estimator
- A multivariate generalization of the power exponential family of distributions
This page was built for publication: Modified likelihood ratio tests in heteroskedastic multivariate regression models with measurement error
