Man pages for DataScienceForPublicPolicy/unitrootML
unitrootML - Machine Learning-Based Hypothesis Testing for Time Series
| dgp_ar1_mae | Generate data according to Equation 1 page 183 of Enders. |
| dgp_arma | Generate data according to ARMA process |
| dgp_enders1 | Generate time series with properties according to Equation 1... |
| dgp_enders2 | Generate time series with properties according to Equation 2... |
| dgp_enders3 | Generate time series with properties according to Equation 3... |
| dgp_engle | Generate data according to Heteroskedasticitic error term... |
| gen_bank | Generate a bank of time series for use in a Near Unit... |
| gen_features | Estimate a battery of statistical tests for unit roots and... |
| gen_test | Construct ML models for use as a ML test |
| make_noise | Draw random values from an assortment of distributions |
| ml_test | Apply ML-based hypothesis test to a bank of time series |
| scale_01 | Scale data from (0 to 1) to (0 to 1) |
| scale_inf | Scale a series from (0 to infinity) to (0 to 1) |
| seas_decomp | Extract seasonal decomposition from a time series |
| testing_summary | Return summary of ML-based hypothesis test |
| threshold_calc | Calculate threshold given cost ratios |
| ts_features | Estimate a battery of statistical tests for unit roots and... |
| ts_measures | Calculate time series characteristics |
