DocumentCode
3102976
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
fYear
1988
fDate
3-5 Aug 1988
Firstpage
213
Lastpage
216
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Spectrum Estimation and Modeling, 1988., Fourth Annual ASSP Workshop on
Conference_Location
Minneapolis, MN
Type
conf
DOI
10.1109/SPECT.1988.206194
Filename
206194
Link To Document