Effective warning signals
 Predicting variance of variance by direct calculation  still need to crunch some math for the expected convergence.
 Still, the approach should be able to do more than describe single points as unexpected deviates.
 Still need to address gradual change vs change point analysis.
 Essentially the same as the phyolgenentic problem  one rate vs two rates. Model selection approaches?
 So far theory is essentially built on a model selection between linear models.
 Calculate the eigenvalue directly rather than ratio of eigenvalue to noise:
 Estimate the eigenvalue from the correlation function and from power spectrum, rather than the lag1 autocorrelation, or variance.
 Proper signal processing techniques for detecting bifurcations?
Coding Progress
 Added a proper autocorrelation function calculation, log transform and linear regression gives the eigenvalue and the variance.
 Tested using the Langevin model
Whose correlation function is given by
