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将分层抽样中的样本分配视为博弈
We consider here the problem of allocating sampling effort among strata when there is no useful information on the within-stratum variability. We show that in a natural game theoretic analogue proportional allocation is a unique good strategy.
作为博弈的分层抽样分配
We consider here the problem of allocating sampling effort among strata when there is no useful information on the within-stratum variability. We show that in a natural game theoretic analogue proportional allocation is a unique good strategy.
一般线性模型中若干最小二乘方差估计量的偏差
Watson (1955) investigated the performance of a regression analysis based on the assumption that the error covariance matrix is σ2γ when it is, in fact, σ2γ. In the present paper Watson's results regarding the effects of this type of specification error on the bias of estimators of variance are generalized. In particular, we give, for arbitrary design matrices of full rank, attainable bounds for the bias of the least-squares estimator of the variance of arbitrary linear…
一般线性模型中若干最小二乘方差估计量的偏差
Watson (1955) investigated the performance of a regression analysis based on the assumption that the error covariance matrix is σ2γ when it is, in fact, σ2γ. In the present paper Watson's results regarding the effects of this type of specification error on the bias of estimators of variance are generalized. In particular, we give, for arbitrary design matrices of full rank, attainable bounds for the bias of the least-squares estimator of the variance of arbitrary linear…