Detecting difference between coefficients in linear model using jackknife empirical likelihood
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Publication:328099
DOI10.1007/s11424-015-3313-zzbMath1348.62202OpenAlexW768322681MaRDI QIDQ328099
Sanguo Zhang, Xinqi Wu, Qing-Zhao Zhang
Publication date: 20 October 2016
Published in: Journal of Systems Science and Complexity (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s11424-015-3313-z
Linear regression; mixed models (62J05) Nonparametric estimation (62G05) Nonparametric tolerance and confidence regions (62G15)
Uses Software
Cites Work
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- Adaptive profile-empirical-likelihood inferences for generalized single-index models
- Two-sample empirical likelihood method for difference between coefficients in linear regression model
- The EFM approach for single-index models
- Efficient empirical-likelihood-based inferences for the single-index model
- Empirical likelihood ratio confidence regions
- An empirical likelihood-based method for comparison of treatment effects-test of equality of coefficients in linear models
- On the accuracy of empirical likelihood confidence regions for linear regression model
- Semi-empirical likelihood ratio confidence intervals for the difference of two sample means
- An unbalanced jackknife
- Empirical likelihood is Bartlett-correctable
- Some new methods for the comparison of two linear regression models
- Empirical likelihood for single-index models
- Tests of Equality Between Sets of Coefficients in Two Linear Regressions
- Empirical Likelihood Confidence Regions in a Partially Linear Single-Index Model
- On the level-error after Bartlett adjustment of the likelihood ratio statistic
- Empirical likelihood ratio confidence intervals for a single functional
- Jackknife Empirical Likelihood
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