时间戳

首页 > 解决方案 > 使用 pyton 自动估计 auto_arima 中的最佳参数

python - 使用 pyton 自动估计 auto_arima 中的最佳参数

问题描述

任何人都可以帮助我估计自动 arima 的最佳参数。

我正在使用以下脚本，但不确定如何从模型摘要中提取最佳参数。

from pmdarima import auto_arima 

# Fit auto_arima function to dataset 
stepwise_fit = auto_arima(dataset['column1'], start_p = 1, start_q = 1, 
                          max_p = 3, max_q = 3, m = 12, 
                          start_P = 0, seasonal = True, 
                          d = None, D = 1, trace = True, 
                          error_action ='ignore',   # we don't want to know if an order does not work 
                          suppress_warnings = True,  # we don't want convergence warnings 
                          stepwise = True)           # set to stepwise 

# To print the summary 
stepwise_fit.summary()

<class 'statsmodels.iolib.summary.Summary'>
"""
                                      SARIMAX Results                                       
============================================================================================
Dep. Variable:                                    y   No. Observations:                  323
Model:             SARIMAX(1, 0, 0)x(0, 1, [1], 12)   Log Likelihood               -2989.363
Date:                              Fri, 22 May 2020   AIC                           5986.726
Time:                                      16:14:35   BIC                           6001.685
Sample:                                           0   HQIC                          5992.705
                                              - 323                                         
Covariance Type:                                opg                                         
==============================================================================

请指教。

标签： pythontime-seriespmdarima

解决方案

你应该做：

stepwise_fit.order 
stepwise_fit.seasonal_order

推荐阅读