Man pages for DataScienceForPublicPolicy/hypML
unitrootML - Machine Learning-Based Hypothesis Testing for Time Series

dgp_ar1_maeGenerate data according to Equation 1 page 183 of Enders.
dgp_armaGenerate data according to ARMA process
dgp_enders1Generate time series with properties according to Equation 1...
dgp_enders2Generate time series with properties according to Equation 2...
dgp_enders3Generate time series with properties according to Equation 3...
dgp_engleGenerate data according to Heteroskedasticitic error term...
gen_bankGenerate a bank of time series for use in a Near Unit...
gen_featuresEstimate a battery of statistical tests for unit roots and...
gen_testConstruct ML models for use as a ML test
make_noiseDraw random values from an assortment of distributions
ml_testApply ML-based hypothesis test to a bank of time series
scale_01Scale data from (0 to 1) to (0 to 1)
scale_infScale a series from (0 to infinity) to (0 to 1)
seas_decompExtract seasonal decomposition from a time series
testing_summaryReturn summary of ML-based hypothesis test
threshold_calcCalculate threshold given cost ratios
ts_featuresEstimate a battery of statistical tests for unit roots and...
ts_measuresCalculate time series characteristics
DataScienceForPublicPolicy/hypML documentation built on Dec. 17, 2021, 4:06 p.m.