对于scipy.stats中的python截断正态分布，KSI测试失败

Question

我正在尝试对一组数据进行许多不同分布的KSI测试。我要执行的测试可以在此处的堆栈溢出问题中找到：

How to find probability distribution and parameters for real data? (Python 3)

不幸的是，当我尝试将“ truncnorm”添加到要尝试的分布列表中时，代码无法找到截断正态分布的参数和p值。 P值始终为零。

有人可以帮我吗？

谢谢！

$query

当我尝试运行时：

print('Getting Best Fit')
def get_best_distribution(data):
    dist_names = ["norm", "truncnorm", "exponweib", "weibull_max", "weibull_min", "pareto", "genextreme"]
    dist_results = []
    params = {}
    for dist_name in dist_names:
        dist = getattr(stats, dist_name)
        param = dist.fit(data)

        params[dist_name] = param
        # Applying the Kolmogorov-Smirnov test
        D, p = stats.kstest(data, dist_name, args=param)
        print("p value for "+dist_name+" = "+str(p))
        dist_results.append((dist_name, p))

    # select the best fitted distribution
    best_dist, best_p = (max(dist_results, key=lambda item: item[1]))
    if math.isnan(best_p) == True:
        print('skipping')
        return 'None', 'None', 'None'
    # store the name of the best fit and its p value

    else:
        print("Best fitting distribution: "+str(best_dist))
        print("Best p value: "+ str(best_p))
        print("Parameters for the best fit: "+ str(params[best_dist]))
        print('\n')

        return best_dist, best_p, params[best_dist]

我得到：

param = dist.fit(data)