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Unformatted text preview: t that produces an unbiased estimate of . 2. Show that a complete statistic is minimal. 3. Assume that in a given problem n independent vector samples r m , m = 1, 2, … , n , are available for processing. Each vector has a distribution of the form ? ( ± ²  ³ ) = ´ ( ³ ) µ ( ± ² )exp ( ∑ ? ¶ ( ³ ) · ¶ ( ± ² )). ¸ ¶ =1 The functions p i ( ) and t i ( r m ) are scalar functions of θ and r m respectively. Show that the statistic T( r ) = [T 1 ( r ) T 2 ( r ) … T k ( r )] where ¹ ¶ ( ± ) = ∑ · ¶ ( º » ) ¼ ² =1 is sufficient and complete for . Note that the dimension of the statistic is k and is independent of the number n of vector samples available for processing....
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This note was uploaded on 06/04/2010 for the course EE 8581 taught by Professor Staff during the Spring '08 term at Minnesota.
 Spring '08
 Staff

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