0

我试图了解如何使用 symfit 来拟合一些数据，然后运行下一个示例：

from symfit import Parameter, Variable, exp
from symfit.core.objectives import LogLikelihood
import numpy as np

# Define the model for an exponential distribution (numpy style)
beta = Parameter('beta')
x = Variable('x')
model = (1 / beta) * exp(-x / beta)

# Draw 100 samples from an exponential distribution with beta=5.5
data = np.random.exponential(5.5, 100)

# Do the fitting!
fit = Fit(model, data, objective=LogLikelihood)
fit_result = fit.execute()

从这个页面：https://symfit.readthedocs.io/en/stable/fitting_types.html我收到下一个错误：

AttributeError：“Derivative”对象没有属性“derivative_count”

这个例子有什么问题？

4

0 回答 0