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QUESTION 3 3.1 Consider the model yij = i +eij, i = 1,..., a; j = 1, ..., ni. 3.1.1 Show that u; is estimable. [32 Marks] (7) 3.1.2 Find the best linear unbiased estimator (b.l.u.e) of μi. (5) 3.2 Consider n serially correlated observations y; from a normal population. This means that: E [yi] =μ and var (yi) = 0²; the correlation coefficient between y; and y₁+1 is p for i = 1,, n 1; and that all other correlation coefficients are zero. Show that: 3.2.1 E[y]=; - 3.2.2 Var ()= [1 + 2p (1 − 1)]; and (5) ཆེསྱེÊ (7) 3.2.3 E [S2] = 0² (124), where s² is unbiased estimator of σ². (8)

QUESTION 3 3.1 Consider the model yij = i +eij, i = 1,..., a; j = 1, ..., ni. 3.1.1 Show that u; is estimable. [32 Marks] (7) 3.1.2 Find the best linear unbiased estimator (b.l.u.e) of μi. (5) 3.2 Consider n serially correlated observations y; from a normal population. This means that: E [yi] =μ and var (yi) = 0²; the correlation coefficient between y; and y₁+1 is p for i = 1,, n 1; and that all other correlation coefficients are zero. Show that: 3.2.1 E[y]=; - 3.2.2 Var ()= [1 + 2p (1 − 1)]; and (5) ཆེསྱེÊ (7) 3.2.3 E [S2] = 0² (124), where s² is unbiased estimator of σ². (8)

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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QUESTION 3 3.1 Consider the model yij = i +eij, i = 1,..., a; j = 1, ..., ni. 3.1.1 Show that u; is estimable. [32 Marks] (7) 3.1.2 Find the best linear unbiased estimator (b.l.u.e) of μi. (5) 3.2 Consider n serially correlated observations y; from a normal population. This means that: E [yi] =μ and var (yi) = 0²; the correlation coefficient between y; and y₁+1 is p for i = 1,, n 1; and that all other correlation coefficients are zero. Show that: 3.2.1 E[y]=; - 3.2.2 Var ()= [1 + 2p (1 − 1)]; and (5) ཆེསྱེÊ (7) 3.2.3 E [S2] = 0² (124), where s² is unbiased estimator of σ². (8)
Transcribed Image Text:QUESTION 3 3.1 Consider the model yij = i +eij, i = 1,..., a; j = 1, ..., ni. 3.1.1 Show that u; is estimable. [32 Marks] (7) 3.1.2 Find the best linear unbiased estimator (b.l.u.e) of μi. (5) 3.2 Consider n serially correlated observations y; from a normal population. This means that: E [yi] =μ and var (yi) = 0²; the correlation coefficient between y; and y₁+1 is p for i = 1,, n 1; and that all other correlation coefficients are zero. Show that: 3.2.1 E[y]=; - 3.2.2 Var ()= [1 + 2p (1 − 1)]; and (5) ཆེསྱེÊ (7) 3.2.3 E [S2] = 0² (124), where s² is unbiased estimator of σ². (8)
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