python arma结果怎么看_python中ARMA/ARIMA线性回归模型

这是一个快速的设置，让你开始from statsmodels.tsa.stattools import ARMA

import pandas as pd

import numpy as np

ts = pd.Series(np.random.randn(500), index=pd.date_range('2010-01-01', periods=500))

p, q = 1, 1

arma = ARMA(endog=ts, order=(p, q)).fit()

print arma.summary()

ARMA Model Results

==============================================================================

Dep. Variable: y No. Observations: 500

Model: ARMA(1, 1) Log Likelihood -678.805

Method: css-mle S.D. of innovations 0.941

Date: Tue, 17 May 2016 AIC 1365.610

Time: 00:01:52 BIC 1382.469

Sample: 01-01-2010 HQIC 1372.225

- 05-15-2011

==============================================================================

coef std err z P>|z| [95.0% Conf. Int.]

const 0.0624 0.048 1.311 0.191 -0.031 0.156

ar.L1.y 0.3090 0.311 0.992 0.322 -0.302 0.919

ma.L1.y -0.2177 0.318 -0.684 0.494 -0.841 0.406

Roots

=============================================================================

Real Imaginary Modulus Frequency

-

AR.1 3.2367 +0.0000j 3.2367 0.0000

MA.1 4.5939 +0.0000j 4.5939 0.0000

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