pystra.distributions.gev.GEVmin#
- class GEVmin(name, mean, stdv, shape, input_type=None, startpoint=None)[source]#
Bases:
Distribution
Generalized Extreme Value (GEV) distribution for minima.
This distribution unifies the different types of extreme value distributions: Gumbel (Type I), Fréchet (Type II), and Weibull (Type III).
- Arguments:
name (str): Name of the random variable
mean (float): Mean
stdv (float): Standard deviation
shape (float): Shape parameter. shape < 0.0 is Weibull, shape > 0 is Frechet.
input_type (any): Change meaning of mean and stdv
startpoint (float): Start point for seach
- Raises:
ValueError: If shape is greater than or equal to 0.5
- Notes:
The shape parameter shape must be less than 0.5 for finite variance.
shape < 0 is the Weibull case, shape = 0 is the Gumbel case, and shape > 0 is the Fréchet case.
This distribution is to model minima.
Methods
Cumulative distribution function
getMean
getName
getStartPoint
getStdv
Compute the Jacobian
Probability density function
Plots the PDF of the distribution
Inverse cumulative distribution function
Return a sample of the distribution of length n
setStartPoint
set_location
set_scale
Transformation from u to x
Transformation from x to u
Attributes
std_normal
- jacobian(u, x)#
Compute the Jacobian
- plot(ax=None, **kwargs)#
Plots the PDF of the distribution
- sample(n=1000)#
Return a sample of the distribution of length n
- u_to_x(u)#
Transformation from u to x
- x_to_u(x)#
Transformation from x to u