statsmodels.tsa.base.prediction.PredictionResults¶

class statsmodels.tsa.base.prediction.PredictionResults(predicted_mean, var_pred_mean, dist=None, df=None, row_labels=None)[source]¶

Prediction results

Parameters:

predicted_mean{ndarray, Series, DataFrame}: The predicted mean values
var_pred_mean{ndarray, Series, DataFrame}: The variance of the predicted mean values
dist{None, “norm”, “t”, rv_frozen}: The distribution to use when constructing prediction intervals. Default is normal.
dfint, optional: The degree of freedom parameter for the t. Not used if dist is None, “norm” or a callable.
row_labels{Sequence[Hashable], pd.Index}: Row labels to use for the summary frame. If None, attempts to read the index of predicted_mean

Attributes:

Methods

`conf_int`([alpha])	Confidence interval construction for the predicted mean.
`summary_frame`([alpha])	Summary frame of mean, variance and confidence interval.
`t_test`([value, alternative])	z- or t-test for hypothesis that mean is equal to value

Properties

`predicted_mean`	The predicted mean
`row_labels`	The row labels used in pandas-types.
`se_mean`	The standard deviation of the predicted mean
`tvalues`	The ratio of the predicted mean to its standard deviation
`var_pred_mean`	The variance of the predicted mean