statsmodels.tsa.arima_model.ARIMAResults

class statsmodels.tsa.arima_model.ARIMAResults(model, params, normalized_cov_params=None, scale=1.0)[source]

Methods

conf_int([alpha, cols])

Construct confidence interval for the fitted parameters.

cov_params([r_matrix, column, scale, cov_p, …])

Compute the variance/covariance matrix.

f_test(r_matrix[, cov_p, scale, invcov])

Compute the F-test for a joint linear hypothesis.

forecast([steps, exog, alpha])

Out-of-sample forecasts

initialize(model, params, **kwargs)

Initialize (possibly re-initialize) a Results instance.

load(fname)

Load a pickled results instance

normalized_cov_params()

See specific model class docstring

plot_predict([start, end, exog, dynamic, …])

Plot forecasts

predict([start, end, exog, typ, dynamic])

ARIMA model in-sample and out-of-sample prediction

remove_data()

Remove data arrays, all nobs arrays from result and model.

save(fname[, remove_data])

Save a pickle of this instance.

summary([alpha])

Summarize the Model

summary2([title, alpha, float_format])

Experimental summary function for ARIMA Results

t_test(r_matrix[, cov_p, scale, use_t])

Compute a t-test for a each linear hypothesis of the form Rb = q.

t_test_pairwise(term_name[, method, alpha, …])

Perform pairwise t_test with multiple testing corrected p-values.

wald_test(r_matrix[, cov_p, scale, invcov, …])

Compute a Wald-test for a joint linear hypothesis.

wald_test_terms([skip_single, …])

Compute a sequence of Wald tests for terms over multiple columns.

Properties

aic

arfreq

Returns the frequency of the AR roots.

arparams

arroots

bic

bse

cov_params_default

fittedvalues

hqic

llf

mafreq

Returns the frequency of the MA roots.

maparams

maroots

pvalues

The two-tailed p values for the t-stats of the params.

resid

tvalues

Return the t-statistic for a given parameter estimate.

use_t

Flag indicating to use the Student’s distribution in inference.