# 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

The predicted mean values

var_pred_mean

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
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

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

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