Moment Generating Function of Gamma Distribution
Theorem
Let $X \sim \map \Gamma {\alpha, \beta}$ for some $\alpha, \beta > 0$, where $\Gamma$ is the Gamma distribution.
Then the moment generating function of $X$ is given by:
- $\map {M_X} t = \begin {cases} \paren {1 - \dfrac t \beta}^{-\alpha} & t < \beta \\ \text {does not exist} & t \ge \beta \end {cases}$
Proof
From the definition of the Gamma distribution, $X$ has probability density function:
- $\map {f_X} x = \dfrac {\beta^\alpha x^{\alpha - 1} e^{-\beta x} } {\map \Gamma \alpha}$
From the definition of a moment generating function:
- $\ds \map {M_X} t = \expect {e^{t X} } = \int_0^\infty e^{t x} \map {f_X} x \rd x$
First take $t < \beta$.
Then:
\(\ds \map {M_X} t\) | \(=\) | \(\ds \frac {\beta^\alpha} {\map \Gamma \alpha} \int_0^\infty x^{\alpha - 1} e^{-\paren {\beta - t} x} \rd x\) | ||||||||||||
\(\ds \) | \(=\) | \(\ds \frac {\beta^\alpha} {\map \Gamma \alpha} \int_0^\infty \paren {\frac u {\beta - t} }^{\alpha - 1} e^{-u} \frac {\rd u} {\beta - t}\) | substituting $\paren {\beta - t} x = u$ | |||||||||||
\(\ds \) | \(=\) | \(\ds \frac {\beta^\alpha} {\map \Gamma \alpha \paren {\beta - t}^\alpha} \int_0^\infty u^{\alpha - 1} e^{-u} \rd u\) | ||||||||||||
\(\ds \) | \(=\) | \(\ds \frac {\beta^\alpha \map \Gamma \alpha} {\map \Gamma \alpha \paren {\beta - t}^\alpha}\) | Definition of Gamma Function | |||||||||||
\(\ds \) | \(=\) | \(\ds \paren {\frac \beta {\beta - t} }^\alpha\) | ||||||||||||
\(\ds \) | \(=\) | \(\ds \paren {\frac {\beta - t} \beta}^{-\alpha}\) | ||||||||||||
\(\ds \) | \(=\) | \(\ds \paren {1 - \frac t \beta}^{-\alpha}\) |
$\Box$
Now take $t = \beta$.
Our integral becomes:
\(\ds \frac {\beta^\alpha} {\map \Gamma \alpha} \int_0^\infty x^{\alpha - 1} \rd x\) | \(=\) | \(\ds \frac {\beta^\alpha} {\alpha \map \Gamma \alpha} \bigintlimits {x^\alpha} 0 \infty\) | Primitive of Power, Fundamental Theorem of Calculus | |||||||||||
\(\ds \) | \(=\) | \(\ds 0 + \frac {\beta^\alpha} {\alpha \map \Gamma \alpha} \lim_{x \mathop \to \infty} x^\alpha\) | ||||||||||||
\(\ds \) | \(\to\) | \(\ds \infty\) | for $\alpha > 0$, $x^\alpha$ increases without bound as $x \mathop \to \infty$ |
So $\expect {e^{\beta X} }$ does not exist.
$\Box$
Finally take $t > \beta$.
We have that $-\paren {\beta - t}$ is positive.
As a consequence of Exponential Dominates Polynomial, we have:
- $x^{\alpha - 1} < e^{-\paren {\beta - t} x}$
for sufficiently large $x$.
Therefore, in this case, the integrand increases without bound.
We conclude that the integral is divergent.
Hence $\expect {e^{t X} }$ does not exist for $t > \beta$.
$\blacksquare$
Examples
In the below, $t < \beta$ throughout.
First Moment
The first moment generating function of $X$ is given by:
- $\map { {M_X}'} t = \dfrac {\beta^\alpha \alpha} {\paren {\beta - t}^{\alpha + 1} }$
Second Moment
The second moment generating function of $X$ is given by:
- $\map { {M_X}' '} t = \dfrac {\beta^\alpha \alpha \paren {\alpha + 1} } {\paren {\beta - t}^{\alpha + 2} }$
Third Moment
The third moment generating function of $X$ is given by:
- $\map { {M_X}' ' '} t = \dfrac {\beta^\alpha \alpha \paren {\alpha + 1} \paren {\alpha + 2} } {\paren {\beta - t}^{\alpha + 3} }$
Fourth Moment
The fourth moment generating function of $X$ is given by:
- $\map { {M_X}^{\paren 4} } t = \dfrac {\beta^\alpha \alpha \paren {\alpha + 1} \paren {\alpha + 2} \paren {\alpha + 3} } {\paren {\beta - t}^{\alpha + 4} }$
Sources
- 2014: Christopher Clapham and James Nicholson: The Concise Oxford Dictionary of Mathematics (5th ed.) ... (previous) ... (next): Appendix $13$: Probability distributions
- 2021: Richard Earl and James Nicholson: The Concise Oxford Dictionary of Mathematics (6th ed.) ... (previous) ... (next): Appendix $15$: Probability distributions