statsmodels.stats.anova.anova_lm
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statsmodels.stats.anova.anova_lm(*args, **kwargs)
[source] -
ANOVA table for one or more fitted linear models.
Parameters: args : fitted linear model results instance
One or more fitted linear models
scale : float
Estimate of variance, If None, will be estimated from the largest model. Default is None.
test : str {?F?, ?Chisq?, ?Cp?} or None
Test statistics to provide. Default is ?F?.
typ : str or int {?I?,?II?,?III?} or {1,2,3}
The type of ANOVA test to perform. See notes.
robust : {None, ?hc0?, ?hc1?, ?hc2?, ?hc3?}
Use heteroscedasticity-corrected coefficient covariance matrix. If robust covariance is desired, it is recommended to use
hc3
.Returns: anova : DataFrame
A DataFrame containing. :
See also
model_results.compare_f_test
,model_results.compare_lm_test
Notes
Model statistics are given in the order of args. Models must have been fit using the formula api.
Examples
>>> import statsmodels.api as sm >>> from statsmodels.formula.api import ols
>>> moore = sm.datasets.get_rdataset("Moore", "car", ... cache=True) # load data >>> data = moore.data >>> data = data.rename(columns={"partner.status" : ... "partner_status"}) # make name pythonic >>> moore_lm = ols('conformity ~ C(fcategory, Sum)*C(partner_status, Sum)', ... data=data).fit()
>>> table = sm.stats.anova_lm(moore_lm, typ=2) # Type 2 ANOVA DataFrame >>> print table
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