A Unified Theory of Estimation 1 Rev Extended Feb 1960

Cover A Unified Theory of Estimation 1 Rev Extended Feb 1960
A Unified Theory of Estimation 1 Rev Extended Feb 1960
Allan Birnbaum
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©=1 u=l On the other hand, for any multidecislon problem specified as above, let Q, = Q, (u, ©) > be an arbitrary weight-function; then it. For any multidecislon function © the corresponding Bayes risk is: 61^ .. K k . , • R«(Q, Q*"") =EZEZq(^*®) b(u, e, 9") . Q=l u=l For any given Q" and q(u, Q), vje have R(q, ®'") =IZ Q ' u>a q(u, ©) b(j, o, a'"') + q{u, ©) b(j, o, © J>u u3 u>a ju>« ^(J^-S) = ^ q(u, Q), for j > e, , for j = «, EZ q(u, o), for j Q, and non- increasing in j for j ^ ©; that is,... :(J, '5) has a single relative minimum which it assumes on one or more consecutive values of j including J = ©. Thus each welght-fixnction q(u, o) for the esti- mation problem determines \miquely a weight-function Q{ jj'S) for the multidecision problem^ which has, for each 9, a single relative minim\am» Conversely a weight-function Q. ( j, 0) for the multidecision problem having, for each ©^ a single relative minimum (in the pre- ceding sense) determines ■uniquely (through the last equation) a unique weight-function q(u, o) for the estimation problem.

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