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.

  • df (int, 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

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