Triangular distribution

In probability theory and statistics, the triangular distribution is a continuous probability distribution with lower limit a, upper limit b, and mode c, where a < b and a ≤ c ≤ b.

Triangular

Probability density function
Cumulative distribution function
Parameters	${\displaystyle a:~a\in (-\infty ,\infty )}$ ${\displaystyle b:~a<b\,}$ ${\displaystyle c:~a\leq c\leq b\,}$
Support	${\displaystyle a\leq x\leq b\!}$
PDF	${\displaystyle {\begin{cases}0&{\text{for }}x<a,\\{\frac {2(x-a)}{(b-a)(c-a)}}&{\text{for }}a\leq x<c,\\[4pt]{\frac {2}{b-a}}&{\text{for }}x=c,\\[4pt]{\frac {2(b-x)}{(b-a)(b-c)}}&{\text{for }}c<x\leq b,\\[4pt]0&{\text{for }}b<x.\end{cases}}}$
CDF	${\displaystyle {\begin{cases}0&{\text{for }}x\leq a,\\[2pt]{\frac {(x-a)^{2}}{(b-a)(c-a)}}&{\text{for }}a<x\leq c,\\[4pt]1-{\frac {(b-x)^{2}}{(b-a)(b-c)}}&{\text{for }}c<x<b,\\[4pt]1&{\text{for }}b\leq x.\end{cases}}}$
Mean	${\displaystyle {\frac {a+b+c}{3}}}$
Median	${\displaystyle {\begin{cases}a+{\sqrt {\frac {(b-a)(c-a)}{2}}}&{\text{for }}c\geq {\frac {a+b}{2}},\\[6pt]b-{\sqrt {\frac {(b-a)(b-c)}{2}}}&{\text{for }}c\leq {\frac {a+b}{2}}.\end{cases}}}$
Mode	${\displaystyle c\,}$
Variance	${\displaystyle {\frac {a^{2}+b^{2}+c^{2}-ab-ac-bc}{18}}}$
Skewness	${\displaystyle {\frac {{\sqrt {2}}(a\!+\!b\!-\!2c)(2a\!-\!b\!-\!c)(a\!-\!2b\!+\!c)}{5(a^{2}\!+\!b^{2}\!+\!c^{2}\!-\!ab\!-\!ac\!-\!bc)^{\frac {3}{2}}}}}$
Ex. kurtosis	${\displaystyle -{\frac {3}{5}}}$
Entropy	${\displaystyle {\frac {1}{2}}+\ln \left({\frac {b-a}{2}}\right)}$
MGF	${\displaystyle 2{\frac {(b\!-\!c)e^{at}\!-\!(b\!-\!a)e^{ct}\!+\!(c\!-\!a)e^{bt}}{(b-a)(c-a)(b-c)t^{2}}}}$
CF	${\displaystyle -2{\frac {(b\!-\!c)e^{iat}\!-\!(b\!-\!a)e^{ict}\!+\!(c\!-\!a)e^{ibt}}{(b-a)(c-a)(b-c)t^{2}}}}$