Python 中的 ARIMA 模型

Question

我正在使用 ARIMA 在 Python 中进行预测，以下是我的代码：

import numpy as np 

import pandas as pd 

import matplotlib.pyplot as plt 

from statsmodels.tsa.seasonal import seasonal_decompose

from sklearn import datasets, linear_model

from sklearn.model_selection import train_test_split

HSBC = pd.read_csv('HSBC.csv', index_col = 'Date', parse_dates = True)

HSBC2 = HSBC['Close']

result = seasonal_decompose(HSBC2, model='multiplicative', period = 1)

from pmdarima import auto_arima

import warnings

warnings.filterwarnings("ignore")

stepwise_fit = auto_arima(HSBC2, 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',    

                      suppress_warnings = True,  

                      stepwise = True) 

train = HSBC2[0:173]

test = HSBC2[173:248]

model = SARIMAX(train, order = (0, 1, 1), seasonal_order =(0,1,1,12)) 

result = model.fit()

start = len(train)

end = len(train) + len(test) - 1

prediction = result.predict(start,end,

                            typ = 'levels').rename("Predictions")  

predictions.plot(legend = True) 

test.plot(legend = True)

我很困惑为什么预测图的 x 轴变成数字，它应该是像测试图一样的日期。

Answer 1

如果我没有错，这是由于您没有指定索引的频率。尝试这个：HSBC.index = pd.date_range(freq='d', start=HSBC.index[0], periods=len(HSBC)请注意，如果您的索引是每日间隔的，您应该频率='d'编辑：所以，答案就是改变 predict 方法的参数 start 和 end 参数，例如：start = test['Date'].iloc[0]end = test['Date'].iloc[-1]prediction = result.predict(start,end,                            typ = 'levels').rename("Predictions")