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Unformatted text preview: has breast cancer? 3. Suppose Y = [Y 1 , Y 2 , . .., Y T ] NN T ( : , E ), where E = (1  " )I T + "4 T 4 T N and 4 T is a T×1 vector with each element equal to one and I T is the T×T identity matrix. (5) (a) For what values of " is * E * > 0? (15) (b) Is a meansquare consistent estimator of : ? Why or why not? 4. Consider a random sample Y t (t = 1, 2, . .., T) from a distribution with p.d.f.: where r > 0 is known and 2 is unknown. 2 (5) (a) Find the distribution of . (10) (b) Find the maximum likelihood estimator of 2 . (5) (c) Is an unbiased estimator of 2 ? (10) (d) Does achieve the CramerRao lower bound in finite samples? (20) 5. Consider Question 1 of your computer homework assignment. Attach your answers to parts (g), (h), (i), and (j)....
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 Fall '10
 DaleJ.POIRIER
 Econometrics, Normal Distribution, Maximum likelihood, Estimation theory, Bias of an estimator, positive test results

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