Abstract
For the generalized linear model, the authors propose a sequential sampling procedure based on an adaptive shrinkage estimate of parameter. This method can determine a minimum sample size under which effective variables contributing to the model are identified and estimates of regression parameters achieve the required accuracy. The authors prove that the proposed sequential procedure is asymptotically optimal. Numerical simulation studies show that the proposed method can save a large number of samples compared to the traditional sequential approach.
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This research was supported by the National Natural Science Foundation of China under Grant No. 11101396, the State Key Program of National Natural Science of China under Grant No. 11231010, and the Fundamental Research Funds for the Central Universities under Grant No. WK2040000010.
This paper was recommended for publication by Editor SUN Liuquan.
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Lu, H., Wang, Z. & Wu, Y. Sequential estimate for generalized linear models with uncertain number of effective variables. J Syst Sci Complex 28, 424–438 (2015). https://doi.org/10.1007/s11424-015-3110-8
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DOI: https://doi.org/10.1007/s11424-015-3110-8