Let Xt be an /-dimensional ARMA (p, q) process. Let g: U l -> W be a measurable function. Define a process Zt by Zt = g(Xt). Generally, Z.is not an ARMA process. However, we are interested in such functions g, for which Zt is also an AR process. It is important to know the orders of the process Zt. In the most cases we find only some bounds for them. From the practical point of view, our consid...

It is well-established that the …nancial time series display some stylized fatcs such as volatility clustering, high kurtosis, low starting and slow-decaying autocorrelation function and the Talyor e¤ect as well. In order to evaluate volatility models’capacity in capturing such facts, we apply both standard and robust measures of kurtosis and autocorrelation of squares to GARCH, EGARCH and ARSV...

The space of rational matrices with xed size and degree is shown to have a manifold structure with bers over a Grassmannian. The bers are homeomorphic to a suitable space of strictly proper rational matrices. This structure is compatible with Willems' partition of external variables into inputs and outputs.

High-level resistance to aminoglycosides produced by 16S rRNA methylases in Enterobacteriaceae isolates was investigated. The prevalences of armA in Escherichia coli, Klebsiella pneumoniae, and Enterobacter cloacae were 0.6%, 3.0%, and 10%, respectively. rmtB was more prevalent than armA. Pulsed-field gel electrophoresis patterns indicated that armA and rmtB have spread horizontally and clonally.

An analytically simple and tractable formula for the start-up autocovariances of periodic ARMA (P ARMA) models is provided.