The stability of generally defined nonlinear time series is of interest as nonparametric and other nonlinear methods are used more and more to fit time series. We provide sufficient conditions for stability or nonstability of general nonlinear AR(1) models having delay d[greater-or-equal,...

In order to predict unobserved values of a linear process with infinite variance, we introduce a linear predictor which minimizes the dispersion (suitably defined) of the error distribution. When the linear process is driven by symmetric stable white noise this predictor minimizes the scale...

We present a formulation of subexponential and exponential tail behavior for multivariate distributions. The definitions are necessarily in terms of vague convergence of Radon measures rather than of ratios of distribution tails. With the proper setting, we show that if all one dimensional...