Proof: Characteristic function of a function of a random variable
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Characteristic function of arbitrary function
Metadata: ID: P259 | shortcut: cf-fct | author: JoramSoch | date: 2021-09-22, 09:12.
Theorem: Let $X$ be a random variable with the expected value function $\mathrm{E}_X[\cdot]$. Then, the characteristic function of $Y = g(X)$ is equal to
\[\label{eq:cf-fct} \varphi_Y(t) = \mathrm{E}_X \left[ \mathrm{exp}(it \, g(X)) \right] \; .\]Proof: The characteristic function is defined as
\[\label{eq:cf} \varphi_Y(t) = \mathrm{E} \left[ \mathrm{exp}(it \, Y) \right] \; .\]Due of the law of the unconscious statistician
\[\label{eq:mean-lotus} \begin{split} \mathrm{E}[g(X)] &= \sum_{x \in \mathcal{X}} g(x) f_X(x) \\ \mathrm{E}[g(X)] &= \int_{\mathcal{X}} g(x) f_X(x) \, \mathrm{d}x \; , \end{split}\]$Y = g(X)$ can simply be substituted into \eqref{eq:cf} to give
\[\label{eq:cf-fct-qed} \varphi_Y(t) = \mathrm{E}_X \left[ \mathrm{exp}(it \, g(X)) \right] \; .\]∎
Sources: - Taboga, Marco (2017): "Functions of random vectors and their distribution"; in: Lectures on probability and mathematical statistics, retrieved on 2021-09-22; URL: https://www.statlect.com/fundamentals-of-probability/functions-of-random-vectors.
Metadata: ID: P259 | shortcut: cf-fct | author: JoramSoch | date: 2021-09-22, 09:12.