pyhmc.integrated_autocorr2

pyhmc.integrated_autocorr2(x)

Estimate the integrated autocorrelation time, \(\tau_{int}\) of a time series.

This method estimates the spectral density at zero frequency by fitting an AR(p) model, with p selected by AIC.

Parameters:

x : ndarray, shape=(n_samples, n_dims)

The time series, with time along axis 0.

Returns:

tau_int : ndarray, shape=(n_dims,)

The estimated integrated autocorrelation time of each dimension in x, considered independently.

References

[R5]	Plummer, M., Best, N., Cowles, K., and Vines, K. (2006). CODA: Convergence diagnosis and output analysis for MCMC. R News, 6(1):7-11.