Detecting Changes in Autocorrelated and Fluctuating Signals
bestParameters
L2 error estimation
Generate a Random Walk + AR realization
Generating data from a sinusoidal model with changes
Main DeCAFS algorithm for detecting abrupt changes
Estimate parameter in the Random Walk Autoregressive model
Variance estimation for diff k operators
RW and AR(1) variance estimations with fixed AR(1) parameter
Guided Model Selection
DeCAFS Plotting
Generate a piecewise constant signal of a given length
Detect abrupt changes in time series with local fluctuations as a random walk process and autocorrelated noise as an AR(1) process. See Romano, G., Rigaill, G., Runge, V., Fearnhead, P. (2021) <doi:10.1080/01621459.2021.1909598>.