This paper presents a method to improve implementation accuracy of a recently proposed CORDIC ARMA lattice filter. Since the CORDIC ARMA lattice filter algorithm has a problem in its shift sequence, i t cannot implement a lattice filter accurately. Therefore, in this paper we apply the shift sequence proposed by Walther without the problem to the CORDIC ARMA lattice filter, and then we realize ...

We consider a strictly stationary sequence of random vectors whose finite-dimensional distributions are jointly regularly varying with some positive index. This class of processes includes, among others, ARMA processes with regularly varying noise, GARCH processes with normally or Student-distributed noise and stochastic volatility models with regularly varying multiplicative noise. We define a...

Spatial autoregressive moving average (ARMA) processes have been extensively used in several applications in image/signal processing. In particular, these models have been used for image segmentation, edge detection and image filtering. Image restoration algorithms based on robust estimation of a two-dimensional process have been developed (Kashyap & Eom 1988). Also the two-dimensional autoregr...

Autoregressive moving average (ARMA) models are useful statistical tools to examine the dynamical characteristics of ecological time-series data. Here, we illustrate the utility and challenges of applying ARMA (p,q) models, where p is the dimension of the autoregressive component of the model, and q is the dimension of the moving average component. We focus on parameter estimation and model sel...

Some new results on calculating moving average representation (MAR) coefficients and their limiting distribution from estimated vector ARMA processes are presented. The technique is applied to the problem of estimating the coefficients of unanticipated or 'surprise' variables in a single equation for a multi-period expectations horizon. The method naturally conditions the expectations on all pa...

We report armA in an Escherichia coli pig isolate from Spain. The resistance gene was borne by self-transferable IncN plasmid pMUR050. Molecular analysis of the plasmid and of the armA locus confirmed the spread of this resistance determinant.

The Kalman filter is the celebrated algorithm giving a recursive solution of the prediction problem for time series. After a quite general formulation of the prediction problem, the contributions of its solution by the great mathematicians Kolmogorov and Wiener are shorthly recalled and it is showed as Kalman filter furnishes the optimal predictor, in the sense of least squares, for processes w...