[英]How to properly plot the pdf of a beta function in scipy.stats
我正在嘗試將 beta 分布擬合到某些數據,然后 plot beta 分布與數據的擬合程度如何。 但是 output 看起來真的很奇怪而且不正確。
import scipy.stats as stats
import matplotlib.pyplot as plt
x = np.array([0.9999999 , 0.9602287 , 0.8823198 , 0.83825594, 0.92847216,
0.9632976 , 0.90275735, 0.8383094 , 0.9826664 , 0.9141795 ,
0.88799196, 0.9272752 , 0.94456017, 0.90466917, 0.8905505 ,
0.95424247, 0.781545 , 0.9489085 , 0.9578988 , 0.8644015 ])
beta_params = stats.beta.fit(x)
print(beta_params)
#(3.243900357315478, 1.5909897101396109, 0.7270083219563888, 0.27811444901271615
beta_pdf = stats.beta.pdf(x, beta_params[0], beta_params[1], beta_params[2], beta_params[3])
print(beta_pdf)
#[2.70181543 6.8442073 4.98204632 2.82445508 6.76055614 6.75910611
#5.90419012 2.82696622 5.58521916 6.34096675 5.2508072 6.73212694
#6.98854653 5.98225724 5.36937625 6.9519977 0.67812362 6.99116729
#6.89484982 4.10113147]
plt.plot(x, beta_pdf)
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