Solved

Your Textbook States That an Implication of the Gauss-Markov Theorem

Question 36

Essay

Your textbook states that an implication of the Gauss-Markov theorem is that the sample average, Your textbook states that an implication of the Gauss-Markov theorem is that the sample average,   ,is the most efficient linear estimator of E(Yi)when Y1,... ,Yn are i.i.d.with E(Yi)= μY and var(Yi)=   .This follows from the regression model with no slope and the fact that the OLS estimator is BLUE. Provide a proof by assuming a linear estimator in the Y's,   (a)State the condition under which this estimator is unbiased. (b)Derive the variance of this estimator. (c)Minimize this variance subject to the constraint (condition)derived in (a)and show that the sample mean is BLUE. ,is the most efficient linear estimator of E(Yi)when Y1,... ,Yn are i.i.d.with E(Yi)= μY and var(Yi)= Your textbook states that an implication of the Gauss-Markov theorem is that the sample average,   ,is the most efficient linear estimator of E(Yi)when Y1,... ,Yn are i.i.d.with E(Yi)= μY and var(Yi)=   .This follows from the regression model with no slope and the fact that the OLS estimator is BLUE. Provide a proof by assuming a linear estimator in the Y's,   (a)State the condition under which this estimator is unbiased. (b)Derive the variance of this estimator. (c)Minimize this variance subject to the constraint (condition)derived in (a)and show that the sample mean is BLUE. .This follows from the regression model with no slope and the fact that the OLS estimator is BLUE.
Provide a proof by assuming a linear estimator in the Y's, Your textbook states that an implication of the Gauss-Markov theorem is that the sample average,   ,is the most efficient linear estimator of E(Yi)when Y1,... ,Yn are i.i.d.with E(Yi)= μY and var(Yi)=   .This follows from the regression model with no slope and the fact that the OLS estimator is BLUE. Provide a proof by assuming a linear estimator in the Y's,   (a)State the condition under which this estimator is unbiased. (b)Derive the variance of this estimator. (c)Minimize this variance subject to the constraint (condition)derived in (a)and show that the sample mean is BLUE. (a)State the condition under which this estimator is unbiased.
(b)Derive the variance of this estimator.
(c)Minimize this variance subject to the constraint (condition)derived in (a)and show that the sample mean is BLUE.

Correct Answer:

verifed

Verified

(a)E( blured image )= blured image = μY blured image .Hence for this to be a...

View Answer

Unlock this answer now
Get Access to more Verified Answers free of charge

Related Questions