A new liu type of estimator for the restricted SUR estimator
Journal of Modern Applied Statistical Methods, ISSN: 1538-9472, Vol: 18, Issue: 1, Page: 2-11
2019
- 390Usage
- 3Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Usage390
- Downloads288
- Abstract Views102
- Captures3
- Readers3
Article Description
A new Liu type of estimator for the seemingly unrelated regression (SUR) models is proposed that may be used when estimating the parameters vector in the presence of multicollinearity if the it is suspected to belong to a linear subspace. The dispersion matrices and the mean squared error (MSE) are derived. The new estimator may have a lower MSE than the traditional estimators. It was shown using simulation techniques the new shrinkage estimator outperforms the commonly used estimators in the presence of multicollinearity.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85087077190&origin=inward; http://dx.doi.org/10.22237/jmasm/1556669340; https://jmasm.com/index.php/jmasm/article/view/1024; https://digitalcommons.wayne.edu/jmasm/vol18/iss1/12; https://digitalcommons.wayne.edu/cgi/viewcontent.cgi?article=2758&context=jmasm; https://dx.doi.org/10.22237/jmasm/1556669340
The Netherlands Press
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