Please, I need advice on how to work this problem. thanks

(10.2.9) ARE(OM, 0) = [Eov ( X - do)l' ( 0| X ) 12 Eov(X - 0)2Eol'(0 X)2- 1 From (10.2.9) we know that an M-estimator can never be more efficient than a maximum likelihood estimator. However, we also know when it can be as efficient. a. Show that (10.2.9) is an equality if we choose (x - 0) =cL'(0|x), where L is the log likelihood and c is a constant. b. For each of the following distributions, verify that the corresponding functions give asymptotically efficient M-estimator. i. Normal: f(x)=e-x2/2/(V2n, w/(x)=x ii. Logistic: f(x)= e -* (1+e-x)z, 4(x)=tanh(x), where tanh(x) is the hyperbolic tangent iii. Cauchy: f(x)=[m(1 + x2)] , /(x)=2x/(1+x2) iv. Least informative distribution: f (x )= ] Cx-x2/2 1x| sc (Ce-elx|+c2/2 x/> c with (x)=max{-c, min(c,x)} and C and c are constants. (See Huber 1981, section 3.5, for more details.)