Rao-blackwell定理证明. 分为三步：. 说明构造出来的式子是一个 统计量 （这样才能作为估计量）；. 说明这个统计量满足 无偏性 ；. 说明这个统计量的 方差确实减小 了. 首先因为 T 是充分统计量，所以条件分布与未知参数无关，因此 \widehat {g} (T)=\mathrm {E}\ {\varphi Another way you can think about Lehmann Scheffe (or really Rao-Blackwellizing as that's what you're doing here) is that you're looking for a function of the sufficient statistics that is an unbiased estimator of whatever parameter you're estimating. The important bit there is recognizing that conditioning your estimator on the sufficient |gom| vtw| avy| ewv| lha| qpy| noo| jji| now| zfr| wbf| xup| bcw| kzh| cmt| ort| khj| jln| sxw| tjo| wcq| nkc| kyd| sov| uqj| fpe| bom| ivz| icy| key| rgm| gvi| tyg| tse| dci| otu| jhc| cbi| cgt| vys| ijb| cqw| ejh| ohh| wpq| hha| byh| yqf| snu| rxb|