statsmodels.tsa.stattools.adfuller()结构及用法详解

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本文介绍了Python的statsmodels模块，它提供大量统计模型的类和函数，涵盖回归、广义线性模型、离散选择模型等多种功能。还详细解读了statsmodels.tsa.stattools.adfuller()函数，包括迪基 - 福勒检验及各参数含义。

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statsmodels是一个Python模块，提供了大量统计模型的类和函数。主要功能有：

regression: Generalized least squares (including weighted least squares and least squares with autoregressive errors), ordinary least squares.
glm: Generalized linear models with support for all of the one-parameter exponential family distributions.
discrete choice models: Poisson, probit, logit, multinomial logit
rlm: Robust linear models with support for several M-estimators.
tsa: Time series analysis models, including ARMA, AR, VAR
nonparametric : (Univariate) kernel density estimators
datasets: Datasets to be distributed and used for examples and in testing.
PyDTA: Tools for reading Stata .dta files into numpy arrays.
stats: a wide range of statistical tests

statsmodels.tsa.stattools.adfuller(x, maxlag=None, regression='c', autolag='AIC', store=False, regresults=False)

迪基-福勒检验Augmented Dickey-Fuller(ADF) Test

x (array_like*,* 1d) 数据序列
maxlag (int) – Maximum lag which is included in test, default 12*(nobs/100)^{1/4}
regression $^{'} c^{'},^{'} c t^{'},^{'} c t t^{'},^{'} n c^{'}$

Constant and trend order to include in regression
- ’c’ : constant only (default)
- ’ct’ : constant and trend
- ’ctt’ : constant, and linear and quadratic trend
- ’nc’ : no constant, no trend
autolag $^{'} A I C^{'},^{'} B I C^{'},^{'} t - s t a t^{'}, N o n e$
- if None, then maxlag lags are used
- if ‘AIC’ (default) or ‘BIC’, then the number of lags is chosen to minimize the corresponding information criterion
- ’t-stat’ based choice of maxlag. Starts with maxlag and drops a lag until the t-statistic on the last lag length is significant using a 5%-sized test
store (bool) – If True, then a result instance is returned additionally to the adf statistic. Default is False
regresults (bool*,* optional) – If True, the full regression results are returned. Default is False