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📅 最后修改于: 2023-12-03 15:05:05.570000 🧑 作者: Mango
Scipy Stats GenGamma()
Scipy is a powerful Python library that contains a large number of tools and functions designed to solve scientific and mathematical problems. One of these functions is the stats.gengamma() function, which is part of the stats module of Scipy. The stats.gengamma() function generates random variates of the generalized gamma distribution.
Generalized Gamma Distribution
The generalized gamma distribution is a probability distribution that can be used to model a variety of data types. It is a three-parameter distribution that is defined by the probability density function:
where x is the random variable, a, d and p are the parameters of the distribution, and Γ(⋅) is the gamma function.
stats.gengamma()
The stats.gengamma() function in Scipy generates random variates of the generalized gamma distribution. It takes in three parameters, a, c and loc, where a and c are the shape parameters of the distribution and loc is the location parameter. It returns an array of random variates that follow the generalized gamma distribution.
Here is an example code:
import scipy.stats as st
import matplotlib.pyplot as plt
a = 2
c = 1
loc = 0
rv = st.gengamma(a, c, loc)
fig, ax = plt.subplots(1, 1)
x = np.linspace(rv.ppf(0.01), rv.ppf(0.99), 100)
ax.plot(x, rv.pdf(x), 'r-', lw=5, alpha=0.6, label='gengamma pdf')
ax.legend(loc='best', frameon=False)
plt.show()
This code generates a generalized gamma distribution with a=2, c=1 and location parameter, loc=0. It then plots the probability density function of the distribution using Matplotlib.
Conclusion
The stats.gengamma() function in Scipy is a useful tool for generating random variates that follow the generalized gamma distribution. This can be particularly useful in scientific and mathematical applications, where the generalized gamma distribution is often used to model a variety of data types.