A Widely Linear Complex Autoregressive Process of Order One

Two-stage Procedure in P-Order Autoregressive Process

In this paper, the two-stage procedure is considered for autoregressive parameters estimation in the p-order autoregressive model ( AR(p)). The point estimation and fixed-size confidence ellipsoids construction are investigated which are based on least-squares estimators. Performance criteria are shown including asymptotically risk efficient, asymptotically efficient, and asymptotically consist...

Distributed Widely Linear Complex Kalman Filtering

We introduce cooperative sequential state space estimation in the domain of augmented complex statistics, whereby nodes in a network collaborate locally to estimate noncircular complex signals. For rigour, a distributed augmented (widely linear) complex Kalman filter (D-ACKF) suited to the generality of complex signals is introduced, allowing for unified treatment of both proper (rotation invar...

Autoregressive Gaussian Random Vectors of First Order

Valid Resampling of Higher Order Statistics Using Linear Process Bootstrap and Autoregressive Sieve Bootstrap

Abstract. In this paper we show that the linear process bootstrap (LPB) and the autoregressive sieve bootstrap (AR sieve) fail in general for statistics whose large-sample distribution depends on higher order features of the dependence structure rather than just on autocovariances. We discuss why this is still the case under linearity if it does not come along with causality and invertibility w...

A bivariate first-order signed integer-valued autoregressive process