i need the answer quickly 5. Consider the linear regression model with assumptions (i) to (iii) and (iv*).1y'(In - X(X'V-lX)-x'v-1)y .п — р(a) Show that ô can be written as 6(b) Show that E(ô?) = o² for every (B,o²) E Rº × (0, 0).Assumptions(i) X is a non-stochasticn x p matrix with p < n;(ii) the matrix X has rank p, i.e. X is of full column rank;(iii) the elements of the n x 1 vector y are observable random vectors;(iv*) the elements of the n x 1 vector e are non-observable random vari-ables such that E(e) = 0 and Cov(e) = o²V, where V is a knownn x n symmetric positive definite matrix and o? > 0 is an unknown parameter.

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Description: i need the answer quickly 5. Consider the linear regression model with assumptions (i) to (iii) and (iv*).1y'(In - X(X'V-lX)-x'v-1)y .п — р(a) Show that ô can be written as 6(b) Show that E(ô?) = o² for every (B,o²) E Rº × (0, 0).Assumptions(i) X is

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5. Consider the linear regression model with assumptions (i) to (iii) and (iv*). ((X'V-'x)-x'v-)y. 1 -y' (In n - p (a) Show that ô? can be written as o (b) Show that E(ô?) = o² for every (B, o2) E R' x (0, 00).

5. Consider the linear regression model with assumptions (i) to (iii) and (iv*). ((X'V-'x)-x'v-)y. 1 -y' (In n - p (a) Show that ô? can be written as o (b) Show that E(ô?) = o² for every (B, o2) E R' x (0, 00).

Advanced Engineering Mathematics

10th Edition

ISBN:9780470458365

Author:Erwin Kreyszig

Publisher:Erwin Kreyszig

Chapter2: Second-order Linear Odes

Section: Chapter Questions

Problem 1RQ

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Question

i need the answer quickly

5. Consider the linear regression model with assumptions (i) to (iii) and (iv*).
1
y'(In - X(X'V-lX)-x'v-1)y .
п — р
(a) Show that ô can be written as 6
(b) Show that E(ô?) = o² for every (B,o²) E Rº × (0, 0).
Assumptions
(i) X is a non-stochasticn x p matrix with p < n;
(ii) the matrix X has rank p, i.e. X is of full column rank;
(iii) the elements of the n x 1 vector y are observable random vectors;
(iv*) the elements of the n x 1 vector e are non-observable random vari-
ables such that E(e) = 0 and Cov(e) = o²V, where V is a known
n x n symmetric positive definite matrix and o? > 0 is an unknown parameter.

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ISBN:

9780470458365

Author:

Erwin Kreyszig

Publisher:

Wiley, John & Sons, Incorporated