为了证明ols估计量是渐近有效的，我们需要(1)给出一致的估计量但证明它有更大的方差。

To prove that OLS estimators are asymptotically efficient, one needs to (1) present an estimator that is consistent but its variance is larger.

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该方法依据极大似然原理将来自不同母体(均值相同、方差不同)的随机样本有效融合，得到新的母体均值估计量。

According to maximum likelihood theory, it fuses random samples coming from different matrix (same mean different variance) in an effective way, and gains a nwe estimator of matrix mean.

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此估计量能够达到很好的渐进有效性。

This estimator achieves very good gradual validity.

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