1. Given that the density function of a p × 1 normal random vector a is ƒ(x) = (2π)−² | C |¯½ exp 1/(x − μµ)² (¯`-¹²(x − µ)}]}, - show that the m.g.f. of x is M₂(t) = E{exp(t¹x)} = exp· μ+ [txt}, x ERP. t ERP.

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1. Given that the density function of a p × 1 normal random vector x is
ƒ(x) = (2n)−³ | 27 |¯‡ exp{-} (x − µ)²x−¹(x − µ}},
show that the m.g.f. of a is
{ t²u₁ + } t³²_t } ₁
Mr(t) = E{exp(t²x)} = exp
x = R¹,
t ERP.
1/2t. You can
Hint: Make a linear transformation to y = -1/2(x-μ), and set s =
use the fact that if z ~ N₁(0, 1) is a univariate random variable with a standard normal
distribution, then its m.g.f. is M₂(t) = exp(t²/2).
Transcribed Image Text:1. Given that the density function of a p × 1 normal random vector x is ƒ(x) = (2n)−³ | 27 |¯‡ exp{-} (x − µ)²x−¹(x − µ}}, show that the m.g.f. of a is { t²u₁ + } t³²_t } ₁ Mr(t) = E{exp(t²x)} = exp x = R¹, t ERP. 1/2t. You can Hint: Make a linear transformation to y = -1/2(x-μ), and set s = use the fact that if z ~ N₁(0, 1) is a univariate random variable with a standard normal distribution, then its m.g.f. is M₂(t) = exp(t²/2).
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