Title :
Uniqueness considerations in autoregressive modeling with third moments
Author :
Raghuveer, M.R. ; Dianat, S.A.
Author_Institution :
Dept. of Electr. Eng., Rochester Inst. of Technol., NY, USA
Abstract :
The authors note that Yule-Walker equations for autoregressive (AR) modeling with second-moment (auto-correlation) sequences provide necessary and sufficient conditions for exact matching of the autocorrelation samples of a discrete stationary random process with that of the model. However, when AR modeling is done with linear equations that satisfy the necessary conditions for a match between samples of the third-moment sequence of a process and those of the model, these conditions are not sufficient for exact matching. The authors discuss approaches to fit AR models to the samples of the third-moment sequence of a process such that the corresponding third-moment samples of the model indeed match the given samples
Keywords :
correlation methods; statistical analysis; Yule-Walker equations; autocorrelation samples; autoregressive modeling; discrete stationary random process; exact matching; third moments; uniqueness considerations; Autocorrelation; Equations; Sufficient conditions; White noise;
Conference_Titel :
Spectrum Estimation and Modeling, 1988., Fourth Annual ASSP Workshop on
Conference_Location :
Minneapolis, MN
DOI :
10.1109/SPECT.1988.206194
