Let Z1 be N(m₁, σ²) and Z2 be N(m₂, σ²) Gaussian random variables (not
necessarily independent).
(a) Prove that X1 = Z1 + Z2, X2 = Z1 − Z2 are independent Gaussian
random variables.
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Let Z1 be N(m₁, σ²) and Z2 be N(m₂, σ²) Gaussian random variables (not
necessarily independent).
(a) Prove that X1 = Z1 + Z2, X2 = Z1 − Z2 are independent Gaussian
random variables.
Hint: See if you can compute the covariance of X1 and X2.
I thought that independant variables have zero covariance but zero covariance does not imply independance. In which case is it sufficient to show that cov(x1,X2)=0?
For normally distributed random variables, zero covariance implies independence.
ok thanks I didn't know that was the case.
I am not sure how to approach part b of this question.
b)if cov(Z₁,Z₂)=ρσ²
Find the M.G.F of (X₁,X₂)=(2Z₁-Z₂,Z₁+Z₂)
I think you are supposed to assume that Z1 and Z2 have a joint bivariate normal distribution. Under that assumption, 2Z1-Z2 and Z1+Z2 have a joint bivariate normal distribution. I think you can compute the means, standard deviations, and correlation of 2Z1-Z2 and Z1+Z2 from the information given. Then you should be able to find the MGF from a known formula for the MGF of a bivariate normal.
Thanks i figured it out. It was basically what you stated.