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A Unified Monte-Carlo Jackknife for Small Area Estimation after Model Selection by Jiang, Jiming; Lahiri, P.; Nguyen, Thuan is a scholarly article available to read on EtoBox.

What is A Unified Monte-Carlo Jackknife for Small Area Estimation after Model Selection about?

We consider estimation of measure of uncertainty in small area estimation (SAE) when a procedure of model selection is involved prior to the estimation. A unified Monte-Carlo jackknife method, called McJack, is proposed for estimating the logarithm of the mean squared prediction error. We prove the second-order unbiasedness of McJack, and demonstrate the performance of McJack in assessing uncertainty in SAE after model selection through empirical investigations that include simulation studies and real-data analyses.

Author

Jiang, Jiming; Lahiri, P.; Nguyen, Thuan

Published

2016

Language

EN