4. Consider a stateitiral docision peoblion {,D+(,Lf(,d)} for - univenate parameter and loss function f(,d)=g()(a)Z where g()>0 and d in a point stimate of a (a) Show that the Bayes derivion rule ueainat () is dn=B(g())B(()) with corresponding Bayes risk ()=E(()2)E(()){E(())}2 interpreting the resalts for the ras when a()=1. Let X1. Xn te exchangeable so that the X1 are conditionally independent gyem a parameter . Suppose that X4 is distributed as a Weball dirtribution with lenown shape paraneter >0 aud unknown seale parameter >0 dennted WE (x,), with probability density function f(x1)={x121exp(xiH)00.