pymc.Triangular#
- class pymc.Triangular(name, *args, rng=None, dims=None, initval=None, observed=None, total_size=None, transform=UNSET, **kwargs)[source]#
Continuous Triangular log-likelihood.
The pdf of this distribution is
\[\begin{split}\begin{cases} 0 & \text{for } x < a, \\ \frac{2(x-a)}{(b-a)(c-a)} & \text{for } a \le x < c, \\[4pt] \frac{2}{b-a} & \text{for } x = c, \\[4pt] \frac{2(b-x)}{(b-a)(b-c)} & \text{for } c < x \le b, \\[4pt] 0 & \text{for } b < x. \end{cases}\end{split}\](
Source code,png,hires.png,pdf)
Support
\(x \in [lower, upper]\)
Mean
\(\dfrac{lower + upper + c}{3}\)
Variance
\(\dfrac{upper^2 + lower^2 +c^2 - lower*upper - lower*c - upper*c}{18}\)
- Parameters
- lowertensor_like of
float, default 0 Lower limit.
- ctensor_like of
float, default 0.5 Mode.
- uppertensor_like of
float, default 1 Upper limit.
- lowertensor_like of
Methods
Triangular.dist([lower, upper, c])Creates a tensor variable corresponding to the cls distribution.
