本文整理匯總了Python中statsmodels.tsa.arima_process.ArmaProcess.isstationary方法的典型用法代碼示例。如果您正苦於以下問題：Python ArmaProcess.isstationary方法的具體用法？Python ArmaProcess.isstationary怎麽用？Python ArmaProcess.isstationary使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類statsmodels.tsa.arima_process.ArmaProcess的用法示例。
在下文中一共展示了ArmaProcess.isstationary方法的2個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: ArmaProcess
# 需要導入模塊: from statsmodels.tsa.arima_process import ArmaProcess [as 別名]
# 或者: from statsmodels.tsa.arima_process.ArmaProcess import isstationary [as 別名]
# <markdowncell>
# * Let's make sure this models is estimable.
# <codecell>
arma_t = ArmaProcess(arparams, maparams)
# <codecell>
arma_t.isinvertible()
# <codecell>
arma_t.isstationary()
# <rawcell>
# * What does this mean?
# <codecell>
fig = plt.figure(figsize=(12,8))
ax = fig.add_subplot(111)
ax.plot(arma_t.generate_sample(size=50));
# <codecell>
arparams = np.array([1, .35, -.15, .55, .1])
maparams = np.array([1, .65])示例2: ArmaProcess
# 需要導入模塊: from statsmodels.tsa.arima_process import ArmaProcess [as 別名]
# 或者: from statsmodels.tsa.arima_process.ArmaProcess import isstationary [as 別名]
axes[2].set_ylabel('Trend')
self.irregular.plot(ax=axes[3], legend=False)
axes[3].set_ylabel('Irregular')
fig.tight_layout()
return fig
if __name__ == "__main__":
import numpy as np
from statsmodels.tsa.arima_process import ArmaProcess
np.random.seed(123)
ar = [1, .35, .8]
ma = [1, .8]
arma = ArmaProcess(ar, ma, nobs=100)
assert arma.isstationary()
assert arma.isinvertible()
y = arma.generate_sample()
dates = pd.date_range("1/1/1990", periods=len(y), freq='M')
ts = pd.TimeSeries(y, index=dates)
xpath = "/home/skipper/src/x12arima/x12a"
try:
results = x13_arima_analysis(xpath, ts)
except:
print("Caught exception")
results = x13_arima_analysis(xpath, ts, log=False)
# import pandas as pd