随机效应模型中方差分量的非负二次型估计

NONNEGATIVE QUADRATIC ESTIMATES OF VARIANCE COMPONENTS IN RANDOM-EFFECT MODOLS

  • 摘要:Y1,Y2是相互独立的随机变量,Y1/(ασ+τ)~X2n1),Y2/τx2n2),其中σ>0,τ>0是未知方差分量,α>0,正整数n1,n2是已知常数。本文从风险函数及偏差角度研究了σ的无偏估计Y1/(αn1)—Y2/(αn2)的改进,并指出用非负二次估计PY1代替σ的无偏估计较合适,其中p=\min \left\\frac1\left(n_1+2\right) a, \frac1r_1 u \sqrt\frac2\left(n_1+n_2\right)n_2\left(n_1+2\right)\right\,最后把上述结果用于一种方式分组及二级套分类随机效应模型。

     

    Abstract: LetY1,Y2 be independent random variables, and Y1/(ασ+τ)~X2n1), Y2/τx2n2), where σ>0, τ>0 are unknown variance components, α>0, n1, n2 are known positive integers. In this paper improvement of unbiased estimator Y1/(an1)-Y2/(an2) of σ is studied from the points of view of risk function and bias, and it is more suitable to replace the unbiased estimator of σ by nonnegative quadratic estimator pY1, where p=\left(1 / a\left(n_1+2\right), \quad \sqrt2\left(n_1+n_2\right) / n_2\left(n_1+2\right) /\left(a n_1\right)\right).This result is applied to random-effect models of one-way classification, and two-way nested olassification.

     

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