Moment Generating Function of Gaussian Distribution/Examples/Second Moment
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Examples of Use of Moment Generating Function of Gaussian Distribution
Let $X \sim N \paren {\mu, \sigma^2}$ for some $\mu \in \R, \sigma \in \R_{> 0}$, where $N$ is the Gaussian distribution.
The second moment generating function of $X$ is given by:
- $\map { {M_X}} t = \paren {\sigma^2 + \paren {\mu + \sigma^2 t}^2 } \map \exp {\mu t + \dfrac 1 2 \sigma^2 t^2}$
Proof
We have:
\(\ds \map { {M_X}} t\) | \(=\) | \(\ds \frac \d {\d t} \paren {\paren {\mu + \sigma^2 t} \map \exp {\mu t + \dfrac 1 2 \sigma^2 t^2} }\) | Moment Generating Function of Gaussian Distribution: First Moment | |||||||||||
\(\ds \) | \(=\) | \(\ds \sigma^2 \map \exp {\mu t + \dfrac 1 2 \sigma^2 t^2} + \paren {\mu + \sigma^2 t}^2 \map \exp {\mu t + \dfrac 1 2 \sigma^2 t^2}\) | Chain Rule for Derivatives, Derivative of Power, Derivative of Exponential Function, Product Rule for Derivatives | |||||||||||
\(\ds \) | \(=\) | \(\ds \paren {\sigma^2 + \paren {\mu + \sigma^2 t}^2 } \map \exp {\mu t + \dfrac 1 2 \sigma^2 t^2}\) | simplifying |
$\blacksquare$