diff --git a/I/Table_of_Contents.md b/I/Table_of_Contents.md index 176b4788..d400c9fe 100644 --- a/I/Table_of_Contents.md +++ b/I/Table_of_Contents.md @@ -60,6 +60,7 @@ Proofs by **[Number](/I/Proof_by_Number.html)** and **[Topic](/I/Proof_by_Topic.    3.1.1. *[Definition](/D/cuni.html)*
   3.1.2. **[Probability density function](/P/cuni-pdf.html)**
   3.1.3. **[Cumulative distribution function](/P/cuni-cdf.html)**
+    3.1.4. **[Quantile function](/P/cuni-cdf.html)**
3.2. Normal distribution
   3.2.1. *[Definition](/D/norm.html)*
diff --git a/P/cuni-qf.md b/P/cuni-qf.md new file mode 100644 index 00000000..8eb0ff8c --- /dev/null +++ b/P/cuni-qf.md @@ -0,0 +1,62 @@ +--- +layout: proof +mathjax: true + +author: "Joram Soch" +affiliation: "BCCN Berlin" +e_mail: "joram.soch@bccn-berlin.de" +date: 2020-01-02 18:27:00 + +title: "Quantile function of the continuous uniform distribution" +chapter: "Probability Distributions" +section: "Univariate continuous distributions" +topic: "Continuous uniform distribution" +theorem: "Quantile function" + +sources: + +proof_id: "P39" +shortcut: "cuni-qf" +username: "JoramSoch" +--- + + +**Theorem:** Let $X$ be a random variable following a continuous uniform distribution: + +$$ \label{eq:cuni} +X \sim \mathcal{U}(a, b) \; . +$$ + +Then, the quantile function of $X$ is + +$$ \label{eq:cuni-qf} +Q_X(p) = bp + a(1-p) \; . +$$ + + +**Proof:** The [cumulative distribution function of the continuous uniform distribution](/P/cuni-cdf.html) is: + +$$ \label{eq:cuni-cdf} +F_X(x) = +\begin{cases} +\;\; 0 & , \text{if} \; x < a \\ +\frac{x-a}{b-a} & , \text{if} \; a \leq x \leq b \\ +\;\; 1 & , \text{if} \; x > b \; . +\end{cases} +$$ + +Thus, the [quantile function](/D/qf.html) is: + +$$ \label{eq:cuni-qf-s1} +Q_X(p) = F_X^{-1}(x) \; . +$$ + +This can be derived by rearranging equation \eqref{eq:cuni-cdf}: + +$$ \label{eq:cuni-cdf-s2} +\begin{split} +p &= \frac{x-a}{b-a} \\ +x &= p(b-a) + a \\ +x &= bp + a(1-p) = Q_X(p) \; . +\end{split} +$$ \ No newline at end of file