Diebold Mariano test
Project description
Diebold Mariano Test 工具包
特点
通过DM检验的结果,可以判别任意两类算法的预测结果是否存在差异性。
安装
pip install diebold-mariano-test
更新
pip install --upgrade diebold-mariano-test
使用说明
>>> # 导入包
>>> from diebold_mariano_test import *
>>> ori_list = [3, 5, 4, 1] # 原始时间序列数据
>>> a1_list = [2, 3, 4, 2] # 预测算法一得到的时间序列数据
>>> a2_list = [3, 2, 2, 4] # 预测算法二得到的时间序列数据
>>> # 使用MSE方法计算 Diebold-Mariano Test.
>>> d_t_list = cul_d_t(MSE, ori_list, a1_list, a2_list)
>>> print(d_t_list) # 输出中间变量d_t的数值。
[1, -4, -8, -16]
>>> cul_DM(d_t_list) # 输出结果
-2.254898764780173
>>> cul_P(d_t_list) # 输出伴随的P值
0.024139683878213303
>>> # 使用MAE方法计算 Diebold-Mariano Test.
>>> d_t_list = cul_d_t(MAE, ori_list, a1_list, a2_list)
>>> print(d_t_list) # 输出中间变量d_t的数值。
[1, 0, -2, -4]
>>> cul_DM(d_t_list) # 输出结果
-1.4213381090374029
>>> cul_P(d_t_list) # 输出伴随的P值
0.155218489684684
说明
项目发布于PyPI:单击访问
本模块尚不完善,有任何相关问题或建议,欢迎在本项目的github页面中提交issue: 单击访问
License
GNU General Public License v3.0
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