ARMAsel for Detection and Correction of Outliers in Univariate Stochastic Data

For stationary random data, an automatic estimation algorithm can now select a time series model with a spectral accuracy close to the Cramér–Rao lower bound. The parameters of that selected time series model accurately represent the spectral density and the autocovariance function of the data. That is all the possible information for Gaussian...