Fitting & statistics#
Curve fitting, ARIMA, decomposition, correlation and non-Gaussian statistics.
Fitting: Spectral Line Analysis
Fit TimeSeries or FrequencySeries data with iminuit-backed least-squares fitting and error estimation.
ARIMA: Time Series Forecasting
Model and forecast time series with AR, MA, ARMA, and ARIMA/SARIMAX methods added to TimeSeries.
Decomposition Analysis: PCA, ICA, and Eigenmodes
Principal and Independent Component Analysis on TimeSeriesMatrix via pca() / ica().
Correlation Analysis: Statistical Methods
Pearson, Kendall, and other correlation measures between TimeSeries objects for noise hunting and nonlinear coupling.
Non-Gaussian Noise Analysis: Rayleigh and Gaussian-Chi
A non-Gaussian noise analysis toolkit based on Rayleigh and Gaussian-Chi statistics.