statsmodels.tsa.base.prediction.PredictionResults

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

Prediction results

Parameters:

predicted_meanndarray, Series, or DataFrame

The predicted mean values.

var_pred_meanndarray, Series, or DataFrame

The variance of the predicted mean values.

dist“norm”, “t”, or rv_frozen, optional

The distribution to use when constructing prediction intervals. Default is the normal distribution.

dfint, optional

The degrees of freedom parameter for the t distribution. Not used if dist is “norm” or an rv_frozen distribution.

row_labelssequence of hashable or pandas.Index, optional

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