Bispectrum estimation using AR‐modelling

In this paper we present a new autoregressive (AR) method for bispectrum estimation defined in terms of its third‐moment sequence. The method is based on the segmentation of data into coupled records, and can be considered to be a modification of the “third order recursion method”(TOR). Its foundation resides in considering the data of the process at the left and the right of each record (needed for the calculation of third moment sequence) as not null and taking them as the data corresponding to the preceding and succeeding record respectively. Several simulated examples show that this method allows model parameters to be obtained with greater precision, most of all when only few data are available per record. The influence of factors such as number of data and records, model order, and added white and coloured Gaussian noise on the parameters’ estimation is also considered.