scipy.stats.rv_continuous() is a continuous random variable class which is meant for sub-classing. It is a base class for constructing specific distribution from continuous random variables. This class can’t directly be used as a distribution.
Parameters :
moment : [int] moment calculation to use: 0 for pdf, 1 for ppf. Default = 1
a : [float] Lower bound for distribution. Default is -ve infinity.
b : [float] Upper bound for distribution. Default is +ve infinity.
xtol : [float] tolerance for fixed point calculation for ppf
name : [str] Name of the instance. Used to construct the default e.g. for distributions
badvalue : [object] Default is np.nan. Value in a result arrays that indicates a value that for which some argument restriction is violated.
logname : [str] Used as part of theFirst line of the docstring.
extradoc : [str] Used as the last part of the docstring
shapes : [str] Shape of the distribution.Return : Continuous Random Variable Distribution.
Code #1 : Using “rv_continuous class”.
def sample(self, size = 1, random_state = None): """ Return a sample from PDF - Probability Distribution Function. calling - rv_continuous class. """ return self._rv.rvs(size = size, random_state = random_state) |
Code #2 : Creating Gaussian Distribution from rv_continuous.
from scipy.stats import rv_continuous import numpy as np class gaussian_gen(rv_continuous): '''Gaussian distribution''' def _pdf(self, x): return np.exp(-x**2 / 2.) / np.sqrt(2.0 * np.pi) gaussian = gaussian_gen(name = 'gaussian') x = 2.0gaussian._pdf(x) |
Output :
0.05399096651318806
