Moment in terms of Moment Generating Function
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Theorem
Let $X$ be a random variable.
Let $M_X$ be the moment generating function of $X$.
Then:
- $\expect {X^n} = \map { {M_X}^{\paren n} } 0$
where:
- $n$ is a non-negative integer
- ${M_X}^{\paren n}$ denotes the $n$th derivative of $M_X$
- $\expect {X^n}$ denotes the expectation of $X^n$.
Proof
\(\ds \map { {M_X}^{\paren n} } t\) | \(=\) | \(\ds \frac {\d^n} {\d t^n} \expect {e^{t X} }\) | Definition of Moment Generating Function | |||||||||||
\(\ds \) | \(=\) | \(\ds \frac {\d^n} {\d t^n} \expect {\sum_{m \mathop = 0}^\infty \frac {t^m X^m} {m!} }\) | Power Series Expansion for Exponential Function | |||||||||||
\(\ds \) | \(=\) | \(\ds \frac {\d^n} {\d t^n} \sum_{m \mathop = 0}^\infty \expect {\frac {t^m X^m} {m!} }\) | Expectation is Linear | |||||||||||
\(\ds \) | \(=\) | \(\ds \sum_{m \mathop = 0}^\infty \frac {\d^n} {\d t^n} \paren {\frac {t^m} {m!} } \expect {X^m}\) | Expectation is Linear, Power Series is Termwise Differentiable within Radius of Convergence | |||||||||||
\(\ds \) | \(=\) | \(\ds \sum_{m \mathop = n}^\infty \frac {m^{\underline n} t^{m - n} } {m!} \expect {X^m}\) | Nth Derivative of Mth Power | |||||||||||
\(\ds \) | \(=\) | \(\ds \sum_{m \mathop = n}^\infty \frac { m! t^{m - n} } {m! \paren {m - n}!} \expect {X^m}\) | Falling Factorial as Quotient of Factorials | |||||||||||
\(\ds \) | \(=\) | \(\ds \frac {t^{n - n} } {\paren {n - n}!} \expect {X^n} + \sum_{m \mathop = n + 1}^\infty \frac {t^{m - n} } {\paren {m - n}!} \expect {X^m}\) | ||||||||||||
\(\ds \) | \(=\) | \(\ds \expect {X^n} + \sum_{m \mathop = n + 1}^\infty \frac {t^{m - n} } {\paren {m - n}!} \expect {X^m}\) |
Setting $t = 0$ yields the result.
$\blacksquare$
Sources
- 1998: David Nelson: The Penguin Dictionary of Mathematics (2nd ed.) ... (previous) ... (next): moment generating function
- 2008: David Nelson: The Penguin Dictionary of Mathematics (4th ed.) ... (previous) ... (next): moment generating function