statsmodels.tsa.arima_model.ARIMAResults¶
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class
statsmodels.tsa.arima_model.ARIMAResults(model, params, normalized_cov_params=None, scale=1.0)[source]¶ Methods
aic()arfreq()Returns the frequency of the AR roots. arparams()arroots()bic()bse()conf_int([alpha, cols, method])Returns the confidence interval of the fitted parameters. cov_params()f_test(r_matrix[, cov_p, scale, invcov])Compute the F-test for a joint linear hypothesis. fittedvalues()forecast([steps, exog, alpha])Out-of-sample forecasts hqic()initialize(model, params, **kwd)llf()load(fname)load a pickle, (class method) mafreq()Returns the frequency of the MA roots. maparams()maroots()normalized_cov_params()plot_predict([start, end, exog, dynamic, ...])Plot forecasts predict([start, end, exog, typ, dynamic])ARIMA model in-sample and out-of-sample prediction pvalues()remove_data()remove data arrays, all nobs arrays from result and model resid()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 tvalues()Return the t-statistic for a given parameter estimate. 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
aic()arfreq()Returns the frequency of the AR roots. arparams()arroots()bic()bse()conf_int([alpha, cols, method])Returns the confidence interval of the fitted parameters. cov_params()f_test(r_matrix[, cov_p, scale, invcov])Compute the F-test for a joint linear hypothesis. fittedvalues()forecast([steps, exog, alpha])Out-of-sample forecasts hqic()initialize(model, params, **kwd)llf()load(fname)load a pickle, (class method) mafreq()Returns the frequency of the MA roots. maparams()maroots()normalized_cov_params()plot_predict([start, end, exog, dynamic, ...])Plot forecasts predict([start, end, exog, typ, dynamic])ARIMA model in-sample and out-of-sample prediction pvalues()remove_data()remove data arrays, all nobs arrays from result and model resid()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 tvalues()Return the t-statistic for a given parameter estimate. 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 Attributes
use_t