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Vector Autoregressive Moving Average Processes
1991In this chapter, we extend our standard finite order VAR model, $$y_t = \nu + A_1 y_{t - 1} + \ldots + A_p y_{t - p} + \varepsilon _t , $$ by allowing the error terms, here et, to be autocorrelated rather than white noise. The autocorrelation structure is assumed to be of a relatively simple type so that et has a finite order moving average (MA)
openaire +1 more source
Localizable Moving Average Symmetric Stable and Multistable Processes
Stochastic Models, 2009Kenneth J Falconer
exaly
The Cusum of Squares Test for Scale Changes in Infinite Order Moving Average Processes
Scandinavian Journal of Statistics, 2001Sangyeol Lee, Siyun Park
exaly
Gaussian Processes, Moving Averages and Quick Detection Problems
Annals of Probability, 1973Tze Leung Lai
exaly
On the Criteria Functions Used for the Estimation of Moving Average Processes
Journal of the American Statistical Association, 1982Denise R Osborn
exaly +2 more sources
Forward Moving Average Representation in Multivariate MA(1) Processes
Communications in Statistics - Theory and Methods, 2010M Mohammadpour, A R Soltani
exaly

