Adaptation of the jackknifed ridge methods to the linear mixed models
| Autor: | M. Revan Özkale, Özge Kuran |
|---|---|
| Přispěvatelé: | Çukurova Üniversitesi |
| Rok vydání: | 2019 |
| Předmět: |
Statistics and Probability
geography 021103 operations research geography.geographical_feature_category Applied Mathematics 0211 other engineering and technologies 02 engineering and technology jackknifed ridge predictors 01 natural sciences Generalized linear mixed model linear mixed models 010104 statistics & probability ridge predictors Multicollinearity Ridge Modeling and Simulation Statistics 0101 mathematics Statistics Probability and Uncertainty Linear combination Henderson's predictors Mathematics |
| Zdroj: | Journal of Statistical Computation and Simulation. 89:3413-3452 |
| ISSN: | 1563-5163 0094-9655 |
| DOI: | 10.1080/00949655.2019.1669037 |
| Popis: | The purpose of this article is to obtain the jackknifed ridge predictors in the linear mixed models and to examine the superiorities, the linear combinations of the jackknifed ridge predictors over the ridge, principal components regression, r-k class and Henderson's predictors in terms of bias, covariance matrix and mean square error criteria. Numerical analyses are considered to illustrate the findings and a simulation study is conducted to see the performance of the jackknifed ridge predictors. © 2019, © 2019 Informa UK Limited, trading as Taylor & Francis Group. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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