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A suite of statistical tests for time-series data.

Project description

Time Series Statistical Tests

ts-stat-tests

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Motivation

Time Series Analysis has been around for a long time, especially for doing Statistical Testing. Some Python packages are going a long way to make this even easier than it has ever been before. Such as sktime and pycaret and pmdarima and statsmodels.

There are some typical Statistical Tests which are accessible in these Python (QS, Normality, Stability, etc). However, there are still some statistical tests which are not yet ported over to Python, but which have been written in R and are quite stable.

Moreover, there is no one single library package for doing time-series statistical tests in Python.

That's exactly what this package aims to achieve.

A single package for doing all the standard time-series statistical tests.

Tests

Full credit goes to the packages listed in this table.

Type Name Source Package Source Language Implemented
Correlation Auto-Correlation function (ACF) statsmodels Python
Correlation Partial Auto-Correlation function (PACF) statsmodels Python
Correlation Cross-Correlation function (CCF) statsmodels Python
Correlation Ljung-Box test of autocorrelation in residuals (LB) statsmodels Python
Correlation Lagrange Multiplier tests for autocorrelation (LM) statsmodels Python
Correlation Breusch-Godfrey Lagrange Multiplier tests for residual autocorrelation (BGLM) statsmodels Python
Regularity Approximate Entropy antropy python
Regularity Sample Entropy antropy python
Regularity Permutation Entropy antropy python
Regularity Spectral Entropy antropy python
Regularity SVD Entropy antropy python
Seasonality QS seastests R 🔲
Seasonality Osborn-Chui-Smith-Birchenhall test of seasonality (OCSB) pmdarima Python 🔲
Seasonality Canova-Hansen test for seasonal differences (CH) pmdarima Python 🔲
Seasonality Seasonal Strength tsfeatures Python 🔲
Seasonality Trend Strength tsfeatures Python 🔲
Seasonality Spikiness tsfeatures Python 🔲
Stability Stability tsfeatures Python 🔲
Stability Lumpiness tsfeatures Python 🔲
Stationarity Augmented Dickey-Fuller test for stationarity (ADF) statsmodels Python 🔲
Stationarity Kwiatkowski-Phillips-Schmidt-Shin test for stationarity (KPSS) statsmodels Python 🔲
Stationarity Range unit-root test for stationarity (RUR) statsmodels Python 🔲
Stationarity Zivot-Andrews structural-break unit-root test (ZA) statsmodels Python 🔲
Stationarity Phillips-Peron test for stationarity (PP) pmdarima Python 🔲
Stationarity Elliott-Rothenberg-Stock (ERS) de-trended Dickey-Fuller test arch Python 🔲
Stationarity Variance Ratio (VR) test for a random walk arch Python 🔲
Normality Jarque-Bera test of normality (JB) statsmodels Python
Normality Omnibus test for normality (OB) statsmodels Python
Normality Shapiro-Wilk test for normality (SW) scipy Python
Normality D'Agostino & Pearson's test for normality scipy Python
Normality Anderson-Darling test for normality scipy Python
Linearity Harvey Collier test for linearity (HC) statsmodels Python 🔲
Linearity Lagrange Multiplier test for linearity (LM) statsmodels Python 🔲
Linearity Rainbow test for linearity (RB) statsmodels Python 🔲
Linearity Ramsey's RESET test for neglected nonlinearity (RR) statsmodels Python 🔲
Heteroscedasticity Engle's Test for Autoregressive Conditional Heteroscedasticity (ARCH) statsmodels Python 🔲
Heteroscedasticity Breusch-Pagan Lagrange Multiplier test for heteroscedasticity (BPL) statsmodels Python 🔲
Heteroscedasticity Goldfeld-Quandt test for homoskedasticity (GQ) statsmodels Python 🔲
Heteroscedasticity White's Lagrange Multiplier Test for Heteroscedasticity (WLM) statsmodels Python 🔲

Known limitations

  • These listed tests is not exhaustive, and there is probably some more that could be added. Therefore, we encourage you to raise issues or pull requests to add more statistical tests to this suite.
  • This package does not re-invent any of these tests. It merely calls the underlying packages, and calls the functions which are already written elsewhere.

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