Top-level API¶
All public symbols are importable directly from TimeSeriesSRC:
import TimeSeriesSRC as ts
ts.pmodel(...)
ts.estimate(...)
Model building¶
Model assessment¶
Print a parameter table and produce an error-bar plot. |
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Simulate the output of a prediction model driven by white noise. |
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Compute the Akaike Information Criterion (AIC) for a fitted model. |
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Compute the Bayesian Information Criterion (BIC) for a fitted model. |
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Compute the mean squared prediction error (MSE) for a fitted model. |
Time series analysis¶
Compute and plot the ACF, PACF, and GPAC for a univariate time series. |
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Multivariate analysis: impulse response, residual ACF, and GPAC tables. |
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Box-Pierce portmanteau chi-square test on one-step-ahead residuals. |
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Multivariate chi-square tests for transfer function model validation. |
Utilities¶
Apply seasonal (or regular) differencing to a time series. |
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Compute the cross-correlation (or autocorrelation) between two sequences. |
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Compute the partial autocorrelation function via the Levinson-Durbin algorithm. |
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Compute the theoretical autocovariance function of an ARMA process. |
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Compute the Generalized Partial Autocorrelation (GPAC) table. |
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Estimate the impulse response between two sequences (Wiener-Hopf method). |