设X1,X2,···,Xn是来自总体 sim N(mu ,(sigma )^2) 的样本,其中μ已知 (sigma )^2gt 0 为未知参数,样本均值为X,则σ^2的-|||-最大似然估计量为-|||-(A ({sigma )_(i)}^2=dfrac (1)(n-1)sum _(i=1)^n(({X)_(i)-overline (X))}^2. (B) (hat {sigma )}^2=dfrac (1)(n)sum _(i=1)^n(({X)_(i)-overline (X))}^2.-|||-(C ({sigma )_(sigma )}^2=dfrac (1)(n-1)sum _(i=1)^n(({X)_(i)-mu )}^2. (D) (overrightarrow {sigma )}^2=dfrac (1)(n)sum _(i=1)^n(({X)_(i)-mu )}^2.