statsmodels.tsa.arima_model.ARIMAResults¶
-
class
statsmodels.tsa.arima_model.ARIMAResults(model, params, normalized_cov_params=None, scale=1.0)[source]¶ - Attributes
- aic
- arfreq
Returns the frequency of the AR roots.
This is the solution, x, to z = abs(z)*exp(2j*np.pi*x) where z are the roots.
- arparams
- arroots
- bic
- bse
- cov_params_default
- fittedvalues
- hqic
- llf
- mafreq
Returns the frequency of the MA roots.
This is the solution, x, to z = abs(z)*exp(2j*np.pi*x) where z are the 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_tFlag indicating to use the Student’s distribution in inference.
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
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 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.
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
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 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
Returns the frequency of the AR roots.
Returns the frequency of the MA roots.
The two-tailed p values for the t-stats of the params.
Return the t-statistic for a given parameter estimate.
Flag indicating to use the Student’s distribution in inference.