ts-stat-tests 0.5.3

A suite of statistical tests for time-series data.

ts-stat-tests

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 (Normality, Stationarity, Correlation, 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)	arch	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.