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A simplified adaptive fence procedure

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  • Jiang, Jiming
  • Nguyen, Thuan
  • Rao, J. Sunil

Abstract

In this short note, we propose a simplified adaptive fence procedure that reduces the computational burden of the adaptive fence procedure proposed by Jiang et al. [Jiang, J., Rao, J.S., Gu, Z., Nguyen, T., 2008. Fence methods for mixed model selection. Ann. Statist. 36, 1669-1692] for mixed model selection problems. The consistency property of the new procedure is established. Simulation results show that the new procedure performs very well in a small sample situation. The method is applied to a well-known data set in small area estimation.

Suggested Citation

  • Jiang, Jiming & Nguyen, Thuan & Rao, J. Sunil, 2009. "A simplified adaptive fence procedure," Statistics & Probability Letters, Elsevier, vol. 79(5), pages 625-629, March.
    • Handle: RePEc:eee:stapro:v:79:y:2009:i:5:p:625-629
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    References listed on IDEAS

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    1. Florin Vaida & Suzette Blanchard, 2005. "Conditional Akaike information for mixed-effects models," Biometrika, Biometrika Trust, vol. 92(2), pages 351-370, June.
    2. Hamparsum Bozdogan, 1987. "Model selection and Akaike's Information Criterion (AIC): The general theory and its analytical extensions," Psychometrika, Springer;The Psychometric Society, vol. 52(3), pages 345-370, September.
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    1. Jiming Jiang & Thuan Nguyen & J. Sunil Rao, 2015. "The E-MS Algorithm: Model Selection With Incomplete Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(511), pages 1136-1147, September.
    2. Simona Buscemi & Antonella Plaia, 2020. "Model selection in linear mixed-effect models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 104(4), pages 529-575, December.

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