E:\anaconda\lib\site-packages\statsmodels\tsa\base\tsa_model.py:834: ValueWarning: No supported index is available. Prediction results will be given with an integer index beginning at `start`. return get_prediction_index( E:\anaconda\lib\site-packages\arch\__future__\_utility.py:11: FutureWarning: The default for reindex is True. After September 2021 this will change to False. Set reindex to True or False to silence this message. Alternatively, you can use the import comment from arch.__future__ import reindexing to globally set reindex to True and silence this warning. warnings.warn(

这个警告是由于在使用时间序列模型进行预测时，模型没有找到适当的索引。默认情况下，预测结果将使用从“start”开始的整数索引。这通常是因为你没有正确地设置时间序列的索引。建议你检查一下你的代码，确保时间序列的索引设置正确。另外，这个警告还提醒你在未来的一些版本中，reindex参数的默认值将会改变，建议你在代码中指定reindex参数的值。

相关问题

Traceback (most recent call last): File "F:\pythonproject\ARIMA-GRACH\3.py", line 26, in <module> arima_model = ARIMA(train_data, order=(10, 1, 0)) File "E:\anaconda\lib\site-packages\statsmodels\tsa\arima_model.py", line 45, in __init__ super().__init__(*args, **kwargs) File "E:\anaconda\lib\site-packages\statsmodels\tsa\arima_model.py", line 29, in __init__ raise NotImplementedError(ARIMA_DEPRECATION_ERROR) NotImplementedError: statsmodels.tsa.arima_model.ARMA and statsmodels.tsa.arima_model.ARIMA have been removed in favor of statsmodels.tsa.arima.model.ARIMA (note the . between arima and model) and statsmodels.tsa.SARIMAX. statsmodels.tsa.arima.model.ARIMA makes use of the statespace framework and is both well tested and maintained. It also offers alternative specialized parameter estimators.

这个错误是因为你使用了一个已经被弃用的 statsmodels.tsa.arima_model.ARIMA 模型，应该使用新的 statsmodels.tsa.arima.model.ARIMA 模型。你需要更新你的代码来使用新的模型。

具体来说，你需要从 statsmodels.tsa.arima.model 导入 ARIMA，然后创建一个 ARIMA 模型对象，指定 order 参数。示例代码如下：

from statsmodels.tsa.arima.model import ARIMA

arima_model = ARIMA(train_data, order=(10, 1, 0))

这应该可以解决你的问题。

E:\anaconda\lib\site-packages\statsmodels\tsa\base\tsa_model.py:471: ValueWarning: A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting. self._init_dates(dates, freq) E:\anaconda\lib\site-packages\statsmodels\tsa\base\tsa_model.py:471: ValueWarning: A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting. self._init_dates(dates, freq) E:\anaconda\lib\site-packages\statsmodels\tsa\base\tsa_model.py:471: ValueWarning: A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting. self._init_dates(dates, freq)

这是一个ValueWarning警告，意味着你提供了一个日期索引，但没有指定与之相关的频率信息。这在预测时会被忽略。你可以通过设置正确的频率信息来解决这个问题，例如：

import pandas as pd
from statsmodels.tsa.arima_model import ARIMA

# 读取数据并设置日期索引
data = pd.read_csv('data.csv', index_col='date', parse_dates=True)

# 设置正确的频率信息
data.index.freq = 'D'

# 拟合ARIMA模型
model = ARIMA(data, order=(1, 1, 1))
results = model.fit()

# 进行预测
forecast = results.forecast(steps=7)

这里将日期索引的频率设置为“D”表示每天，你可以根据你的数据集设置不同的频率信息。