Expand description
Time series transformations for preprocessing and analysis
This module provides comprehensive transformation methods including:
- Stationarity transformations (Box-Cox, differencing, detrending)
- Normalization and scaling methods
- Stationarity tests (ADF, KPSS)
- Dimensionality reduction techniques
Structs§
- BoxCox
Transform - Box-Cox transformation parameters
- Differencing
Transform - Differencing transformation parameters
- Normalization
Params - Normalization parameters
- Stationarity
Test - Stationarity test results
Enums§
- Normalization
Method - Normalization method
- Stationarity
Test Type - Type of stationarity test
Functions§
- adf_
test - Augmented Dickey-Fuller test for stationarity
- box_
cox_ transform - Apply Box-Cox transformation to time series
- difference_
transform - Apply differencing transformation to make time series stationary
- integrate_
transform - Integrate (reverse difference) a time series
- inverse_
box_ cox_ transform - Inverse Box-Cox transformation
- inverse_
normalize_ transform - Inverse normalization transformation
- kpss_
test - KPSS test for stationarity
- normalize_
transform - Normalize time series using specified method